{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "  #### 画图测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PLT画图测试 plt.plot 说明：https://blog.csdn.net/TeFuirnever/article/details/99672296\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "t = np.arange(0, 5, 0.2)\n",
    "plt.plot(t,t,'o',t,t,'m-')     # k黑色，m紫色\n",
    "plt.plot(t,2*t,'b:')\n",
    "plt.plot(t,t**2,linewidth = 2.0, color = '#000000')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 基于多元线性回归的城市日用水量预测方法 (Python) * \n",
    "----------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 线性回归是什么？举一个简单的例子，有三个变量students, study time, exam score,找出一条曲线拟合这些点。不同的方法有不同的结果,线性回归关注的是最小化误差     \n",
    "   定义一个误差函数E，找出m和d使得E最小（E 即为损失函数）：\n",
    "   $$ \n",
    "   E = \\sum_{i=0}^{n}(y_{i} - (m\\cdot x_{i}+b))^2\n",
    "   $$\n",
    "\n",
    "\n",
    "![](./source/0.png)   \n",
    "\n",
    "通过梯度下降方法，找到E的最小值，解出m,b\n",
    "\n",
    "![](./source/1.png)  \n",
    "\n",
    "   $$ \n",
    "   \\Large m_{new} = m - \\frac{\\partial E}{\\partial m} * L\n",
    "   $$\n",
    "\n",
    "2. 我们需要pandas从Excel文件中加载数据集，使用matplotlib进行可视化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "warnings.filterwarnings('ignore')\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(210, 8)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>实际水量</th>\n",
       "      <th>天气</th>\n",
       "      <th>最高温</th>\n",
       "      <th>最低温</th>\n",
       "      <th>是否为周末</th>\n",
       "      <th>前一天用水量</th>\n",
       "      <th>前8小时用水量</th>\n",
       "      <th>日期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.478867</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.241379</td>\n",
       "      <td>1</td>\n",
       "      <td>0.537982</td>\n",
       "      <td>0.442314</td>\n",
       "      <td>1.549066e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.451904</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>1</td>\n",
       "      <td>0.478867</td>\n",
       "      <td>0.414374</td>\n",
       "      <td>1.549152e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.432096</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>0.034483</td>\n",
       "      <td>0</td>\n",
       "      <td>0.451904</td>\n",
       "      <td>0.390795</td>\n",
       "      <td>1.549238e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.371817</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>0.103448</td>\n",
       "      <td>0</td>\n",
       "      <td>0.432096</td>\n",
       "      <td>0.376177</td>\n",
       "      <td>1.549325e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.367500</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.394737</td>\n",
       "      <td>0.137931</td>\n",
       "      <td>0</td>\n",
       "      <td>0.371817</td>\n",
       "      <td>0.364750</td>\n",
       "      <td>1.549411e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>0.923363</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.758621</td>\n",
       "      <td>0</td>\n",
       "      <td>0.889268</td>\n",
       "      <td>0.855854</td>\n",
       "      <td>1.567037e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>0.940460</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0</td>\n",
       "      <td>0.923363</td>\n",
       "      <td>0.913539</td>\n",
       "      <td>1.567123e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>0.919657</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>1</td>\n",
       "      <td>0.940460</td>\n",
       "      <td>0.888873</td>\n",
       "      <td>1.567210e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>0.863522</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>1</td>\n",
       "      <td>0.919657</td>\n",
       "      <td>0.829210</td>\n",
       "      <td>1.567296e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>0.894872</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0</td>\n",
       "      <td>0.863522</td>\n",
       "      <td>0.828784</td>\n",
       "      <td>1.567382e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         实际水量        天气       最高温       最低温  是否为周末    前一天用水量   前8小时用水量  \\\n",
       "0    0.478867  0.833333  0.263158  0.241379      1  0.537982  0.442314   \n",
       "1    0.451904  0.500000  0.263158  0.068966      1  0.478867  0.414374   \n",
       "2    0.432096  0.333333  0.315789  0.034483      0  0.451904  0.390795   \n",
       "3    0.371817  0.333333  0.315789  0.103448      0  0.432096  0.376177   \n",
       "4    0.367500  0.833333  0.394737  0.137931      0  0.371817  0.364750   \n",
       "..        ...       ...       ...       ...    ...       ...       ...   \n",
       "205  0.923363  1.000000  0.894737  0.758621      0  0.889268  0.855854   \n",
       "206  0.940460  0.833333  0.894737  0.689655      0  0.923363  0.913539   \n",
       "207  0.919657  0.833333  0.763158  0.724138      1  0.940460  0.888873   \n",
       "208  0.863522  0.500000  0.684211  0.689655      1  0.919657  0.829210   \n",
       "209  0.894872  0.500000  0.763158  0.689655      0  0.863522  0.828784   \n",
       "\n",
       "               日期  \n",
       "0    1.549066e+09  \n",
       "1    1.549152e+09  \n",
       "2    1.549238e+09  \n",
       "3    1.549325e+09  \n",
       "4    1.549411e+09  \n",
       "..            ...  \n",
       "205  1.567037e+09  \n",
       "206  1.567123e+09  \n",
       "207  1.567210e+09  \n",
       "208  1.567296e+09  \n",
       "209  1.567382e+09  \n",
       "\n",
       "[210 rows x 8 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('2.xlsx')\n",
    "# Date = data.日期\n",
    "Date = pd.to_datetime(data.日期).astype('int64') / 10**9  # 转换为Unix时间戳\n",
    "data = data.drop(['日期'],axis = 1)\n",
    "data['日期'] = Date\n",
    "train_data = data.iloc[:210]\n",
    "test_data = data.iloc[210:300]\n",
    "train_data_np = train_data.to_numpy()\n",
    "print(train_data_np.shape)\n",
    "train_data.iloc[:] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 0\n",
      "Epoch: 50\n",
      "Epoch: 100\n",
      "Epoch: 150\n",
      "Epoch: 200\n",
      "Epoch: 250\n",
      "Epoch: 300\n",
      "Epoch: 350\n",
      "Epoch: 400\n",
      "Epoch: 450\n",
      "Epoch: 500\n",
      "Epoch: 550\n",
      "最终 m 值: 0.8007738853345887, 最终 b 值: 0.1492806908124057\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3P4aHS716WVtLa0egAQCgEX78UfrsM/fza68N3I0k0TgEGgAAGuHrryXDkBISpAULrK4GBBoAABrBc3YT155pHrj1AQCgxdu6VXrzTfci3kBZvdr9SKBpHgg0AIAWb+JEaeXK4Px2ampwfhf+IdAAAFo0w5A2bnQ/v+EGKSYmcL990knSjTcG7vfQeAQaAECL9sMPUkWF1KaNNHu21L691RUhGFgUDABo0TxX8u3RgzDTkjFCAwAIWatXu+90/eOPdX/n0CH3I4t3WzYCDQAgZOXnS99849t3hw4NaimwGIEGABCyPNNJzz5bf2CJjOTWBC0dgQYAEJIMQyopcT8fNkwaMMDaemAtAg0AoFk6csS9RsazBubnHA7J6ZTCwqTevc2tDc0PgQYA0Czl5koPPdTw93r3ltq1C349aN4INACAZmndOvdjz57uC9idSFiYdMcd5tWE5otAAwBoljzrY/LzpV/8wtJSEAK4sB4AoNmprJS2b3c/79fP2loQGhihAQA0C9OmSevXu58fPOh+TEyse7oJOBaBBgBgudJS6YEHjn8/Lc38WhCaLJlyKi4uVlpamuLi4pSTkyPDMOr9/iOPPCKbzXbc9vHHH5tTMAAgqL76yv3Yvbv08svube5c9yPgC9MDjcvlUnZ2tgYPHqzCwkKVlJQoPz+/3jb33XefKioqvFtRUZESEhI0aNAgc4oGAASVZwFwerr73kzjx0tjx7qnnABfmB5olixZIofDoby8PPXs2VPTpk3TnDlz6m0TERGh2NhY7/bCCy/ozjvvVExMjElVAwCC6V//cj9yA0k0lulraIqKipSenq7IyEhJUmpqqko80dwH5eXlWrRokUpLS+v8jsvlksvl8r52Op2NLxgAEFSzZkn/+If7OYEGjWX6CI3T6VRKSor3tc1mU1hYmCoqKnxq/9JLL2n06NHq2LFjnd+ZPn26YmJivFtycnKT6wYABIcnzEjShRdaVgZCnOmBJjw8XHa7vdZ7ERERqqqqarBtdXW1Zs+erYkTJ9b7vSlTpsjhcHi3HTt2NKlmAEDweO6Y/fHHnKKNxjN9yik+Pl7FxcW13qusrFQ7H27EsWrVKnXq1En9GrjKkt1uPy40AQCan6oq9ynbEtNNaBrTA01aWppePuY8vLKyMrlcLsXHxzfYduHChbr66quDWR4AhCTDkObNk0JtQHrfPnftnTpJCQlWV4NQZnqgyczMlMPh0Pz58zVmzBjl5uYqKytLYWFhcjqdat++vdq2bXvCtkuXLtW8efNMrhgAmr/Vq6Vx46yuovEGDrS6AoQ60wNNeHi4Zs2apdGjRysnJ0fV1dUqKCiQ5D7jacaMGRo5cuRx7b799luVl5crjctGAsBxNm50P552mnTRRdbW4q/wcOnmm62uAqHOklsfjBw5Ulu3blVhYaEyMjKU8L9xxrKysjrb9OzZU0ePHjWpQgAILZ6rX/z619Jjj1lbC2AFy+7llJSUpKSkJKt2DwAtiifQsLAWrRU3pwSAZsYwpNGjpbVrfW+ze7f7kUCD1opAAwDNzHffSQsW+N+uSxepT5/A1wOEAgINADQznumjfv2k117zvV3PnhKX4EJrRaABgGbGE2gGDZLOOsvaWoBQQaAB0CpUVbnv6NzQyZInnSSlpUk2W+P2YxhSYaH7gnGNtWqV+5H1MIDvCDQAWoVbb5Xmz/ftux98IA0f3rj9LF0qXXFF49r+XAN3eQFwDAINgFbBc8ZQ375SZOSJv7Nrl/TDD+6RnMYGGs9+EhOlplyZ4pRTpMsua3x7oLUh0ABo8Y69AeLq1XXfM+iFF6Tbb//p7s+N4Wl7//3SHXc0/ncA+KeN1QUAQLB9/bVvN0D0rFnxLMptDC5wB1iDERqghXvlFfeakLrY7dK990pnnmlaSaaqrpY8t4draE2K5/NvvpGuuaZx+/vmG9/2BSCwCDRAC+ZySRMnSkeO1P+9I0ekt982pyazrVolbd/uft7QvW1PPtm97mXXLmnRosbvs0sXqWvXxrcH4D8CDdCCbd3qDitRUdLTT5/482eflb76yvzazHLs3/bww/V/12aT/vlPqaCgafvMzGz8ad8AGodAA7RgnvUcAwZIEyYc//nOne5As3Wr9N//Su3amVufGTx98OCDUnR0w9/v29e9AQgtBBogBFRUuNeC+Ouzz9yPdS1QTUpyj95UVkobNtR9H6CTTmq+Iw4ul7v+unz5pfuRNS1Ay0agAZq5yZOlP/+5ab9RV6Cx2dyf/d//Sb/4Rd3thw+vf2GxVXbskAYOlByOhr/LWUdAy8Zp20Az9+67TWvfqVP9F4m74QYpvIH/a7NkiXToUNPqCIZVq3wLM2ef7Z52A9ByEWiAZszpdI9CSO57A9XU+L/t2VP/mpDbb3evnzlR2+pqKT7e/XzLFnP+Zn941sdMmlR/H3z6qdS2rbW1AgguAg3QjP373+7Hk0/+aR1LY7aG1NWuTZvAXGwuWI5d9NzUPgAQ2lhDg1bn0CEpP9+90La58yxotXL9R//+7vsTzZ370+0DmotPP3U/sj4GAIEGrc7cudJtt1ldhX8GDrR+38uXu7fmxrOwGUDrRqBBq/P55+7HtDQpNdXaWnzRoYN0zz3W7X/MGPeVdv/zH+tqqM9550mdO1tdBQCrEWjQ6njuhnz33dKvf21tLaEgOlp66imrqwCA+rEoGK2KYXA3ZABoiRihQciprJRGjJDKyvxvaxjSgQPus3dOOy3QlQEArEKgQcj55z+ljz9u2m9kZEh2e0DKAQA0AwQahBzPlNGVV0pTp/rf3maTTj89sDUBAKxFoEHI8QSa886TzjnH2loAAM0DgQZ+2bbN+kvgN3QHaQBA60Oggc/+8x93iKiqsroSt379rK4AANBcWBJoiouLNW7cOH3zzTe6+eab9dRTT8nm481WrrvuOiUkJOj5558PcpX4uU2b3GGmfXvrzxA691ypVy9rawAANB+mBxqXy6Xs7GwNGzZMCxYs0B133KH8/HyNGzeuwbYfffSRVq5cqS1Wz3m0Up61K5dcIr33nrW1AABwLNMvrLdkyRI5HA7l5eWpZ8+emjZtmubMmdNgu0OHDmnSpEnKzc1VbGxs8AvFcbggHQCguTJ9hKaoqEjp6emKjIyUJKWmpqrEc6Ssx+OPP65Dhw4pPDxcK1eu1EUXXVTnNJXL5ZLL5fK+djqdgSk+AEpLpccekw4e9O37bdpI48ZJl10WmP0bhvTwwz9d/t8f//qX+5FAAwBobkwPNE6nUykpKd7XNptNYWFhqqioUFxc3AnbbN++XXl5eTrnnHO0fft2/fnPf9Ypp5yid99994ShZvr06Xr00UeD9jc0xYsvSvn5/rX5/HNp69bA7L+wUHr88ab9xuDBgakFAIBAMT3QhIeHy/6zS7RGRESoqqqqzkCTn5+vxMRELV++XHa7Xb///e916qmnavny5br00kuP+/6UKVN01113eV87nU4lJycH9g9ppN273Y+jRkkXXVT/dw8fdt9A8dtv3Ytx/zeo1STFxe7HAQOkSZP8b9+rFyM0AIDmx/RAEx8fr2LPUfV/Kisr1a5duzrb7Ny5U0OHDvUGoaioKPXu3VulpaUn/L7dbj8uNDUXe/e6H7OzpTFj6v+uYUjTpkn790tffy0NGtT0/Xtm9y6+uHGBBgCA5sj0QJOWlqaXX37Z+7qsrEwul0vx8fF1tklOTq61zqampkY7d+7UqaeeGtRaA8HhkGpq3PcNioz8KdAkJDTc1mZzj4asWeOeKureven1fPml+5FRFgBAS2J6oMnMzJTD4dD8+fM1ZswY5ebmKisrS2FhYXI6nWrfvr3atm1bq82vfvUrDR48WO+8846GDBmi559/Xi6XS+edd57Z5ftl0iRp5kz38/BwaeFC/wKN5L543Jo10i23uLdA4aJ0AICWxPTTtsPDwzVr1ixNnDhRiYmJevvtt5WbmyvJfcbT4sWLj2vTp08f/e1vf9MTTzyh3r17a/HixXrvvfcUFRVldvl+eeutn54fPeq+dou/gebaawOzduZYfftKZ58d2N8EAMBKNsMwDCt2vGvXLhUWFiojI0MJvh7dG8npdComJkYOh0PR0dFB3ZfH3r1S587uaaNXXnGfet23r/Tvf7s///FH34NKdbV72ipQwsPddQEA0Jz5c/y27F5OSUlJSkpKsmr3Qee5zkv37tKQIe7nnjATGenfqEtYmHsDAAAnZvqUU2tx7FV1e/Vyj4p4BHlACgCAVodAEySe20316SO1bVt7EW7XrtbUBABAS2XZlFNLd/iw+9Ez5ee5QrDNJv32t5aVBQBAi0SgCZKjR92PnrUv55/v3gAAQOAx5RQknkATTmQEACDoCDRBQqABAMA8BJogqa52PxJoAAAIPgJNkDBCAwCAeQg0QfLzRcEAACB4CDRBwggNAADmIdAECWtoAAAwD4EmSBihAQDAPASaICHQAABgHgJNkLAoGAAA8xBogoQRGgAAzEOgCRIWBQMAYB4CTZAwQgMAgHkINEFCoAEAwDwEmiBhUTAAAOYh0AQJIzQAAJiHQBMkLAoGAMA8BJogYYQGAADzEGiChEADAIB5CDRBwqJgAADMQ6AJEkZoAAAwD4EmSFgUDACAeQg0QcIIDQAA5iHQBAlraAAAMA+BJkgYoQEAwDwEmiAh0AAAYB5LAk1xcbHS0tIUFxennJwcGYbRYJvs7GzZbDbvlpWVZUKljWMYUk2N+zmBBgCA4DM90LhcLmVnZ2vw4MEqLCxUSUmJ8vPzG2z32Wef6csvv1RFRYUqKir03nvvBb/YRvKc4SQRaAAAMIPpgWbJkiVyOBzKy8tTz549NW3aNM2ZM6feNjt37pRhGDr99NMVGxur2NhYdejQwaSK/eeZbpJYFAwAgBlMDzRFRUVKT09XZGSkJCk1NVUlJSX1tvn0009VXV2tbt26qUOHDrruuutUUVFR5/ddLpecTmetzUzHBhpGaAAACD7TA43T6VRKSor3tc1mU1hYWL0BZcuWLRo8eLA++ugjFRYWqqysTPfff3+d358+fbpiYmK8W3JyckD/hoYQaAAAMJfN8GVFbgDde++9OnLkiPLy8rzvJScna/369UpKSvLpNwoKCjRq1Cjt3bv3hJ+7XC65XC7va6fTqeTkZDkcDkVHRzftD/DB/v1Sp07u59XVUhvOJQMAwG9Op1MxMTE+Hb9NHz+Ij49XcXFxrfcqKyvVrl07n38jNjZW+/btk8vlkt1uP+5zu91+wvfN4hmhsdkIMwAAmMH0w21aWprWr1/vfV1WViaXy6X4+Pg624waNapWmw0bNujkk0+2NLTUh6sEAwBgLtMDTWZmphwOh+bPny9Jys3NVVZWlsLCwuR0OnXkyJHj2qSmpurOO+/U//3f/+mDDz7Q1KlTNWnSJLNL9xkX1QMAwFymH3LDw8M1a9YsjR49Wjk5OaqurlZBQYEkd3CZMWOGRo4cWavNlClTtG3bNl1yySXq3Lmzbr31Vk2ZMsXs0n3GnbYBADCX6YuCPXbt2qXCwkJlZGQoISEhqPvyZ1FRIGzZIvXpI8XGSvWcvAUAAOrRrBcFeyQlJfl8VlOoYcoJAABzcQ5OELAoGAAAcxFogoARGgAAzEWgCQIWBQMAYC4CTRAwQgMAgLkINEFAoAEAwFx+B5otW7YEo44WhUXBAACYy+9Ac8YZZ+iss87Sk08+qdLS0mDUFPIYoQEAwFx+B5p9+/bp/vvv15dffqnBgwdryJAh+tOf/qSdO3cGo76QxKJgAADM5Xeg6dChg0aNGqXXXntNe/bs0c0336zHHntM3bt3V2ZmptatWxeMOkMKIzQAAJirUYfcrVu36p133tG7776rr776Spdffrl+/etfq6qqSqNGjVJ5eXmg6wwpBBoAAMzl9yF34MCB+vbbbzVs2DDdeeedGjFihDp06CBJKi0tDfp9mUIBi4IBADCX34Hm3nvv1VVXXaWoqKjjPktJSVFRUVFACgtlrKEBAMBcfq+hufHGG2uFmT179gS0oJaAKScAAMzld6ApKSnRWWedpbfeekuSNHToUA0YMIDr0xyDKScAAMzld6CZMGGCLr74Yl166aWSpPXr1ys7O1sTJ04MeHGhiiknAADM5fchd9OmTVq4cKFiYmIkuU/jvv3229W/f/+AFxeqGKEBAMBcfo/QDBw4UK+++mqt91599VUNGDAgYEWFOtbQAABgLr8PuS+++KIuv/xyzZs3T927d1dpaakqKiq0dOnSYNQXkphyAgDAXH4fcgcNGqStW7fq/fff165du3TTTTdp+PDhJzyNu7ViygkAAHM1agwhKipKo0ePrvXe3r17uaje/zDlBACAufw+5JaUlCgnJ0dbtmxR9f/mVgzDUHl5uVwuV8ALDEVMOQEAYC6/FwWPGzdOvXv3VmZmpgYPHqwXX3xRERERys3NDUZ9IYkpJwAAzOV3oCkuLtb999+vW265Rdu2bdPll1+ul19+Wfn5+UEoLzQx5QQAgLn8DjSnnXaaXnnlFZ1xxhn69ttvtW/fPnXu3FmlpaXBqC8kMeUEAIC5/A40zz33nGbMmCGn06nx48erR48eOvvss3XVVVcFo76QxJQTAADm8nsM4fzzz9fu3bslSU899ZSGDx+ugwcP6rLLLgt4caGKERoAAMzVqEOuzWbzPr/gggsCVkxLwQgNAADm8nvK6S9/+YvKy8uDUUuLwaJgAADM1ag1NF988UUwamkxmHICAMBcfgeaqVOn6oknntDBgwcbvdPi4mKlpaUpLi5OOTk5MgzD57ZHjhzRwIED9fHHHzd6/8HGlBMAAObyewzhm2++UU1NjXr37q0xY8aoQ4cO3s8eeuihBtu7XC5lZ2dr2LBhWrBgge644w7l5+dr3LhxPu3/qaeeUnFxsb9lm4opJwAAzOX3IbesrEx9+vRRnz59tGfPHr93uGTJEjkcDuXl5SkyMlLTpk3Tbbfd5lOg2bp1q5555hl1797d7/2aiSknAADM5fchd+7cuU3aYVFRkdLT0xUZGSlJSk1NVUlJiU9tJ0yYoPvuu09Lliyp93sul6vWfaWcTmfjC24EppwAADCX34Fm+/btdX52yimnNNje6XQqJSXF+9pmsyksLEwVFRWKi4urs93cuXPlcDh09913Nxhopk+frkcffbTBWoKFKScAAMzl9yG3e/fustls3oW8x16TxnP37Xp3GB4uu91e672IiAhVVVXVGWj27t2rKVOmaOnSpQr3ISVMmTJFd911l/e10+lUcnJyg+0ChSknAADM5fdZTjU1NaqurlZNTY1+/PFHrVq1ShdeeKFWrFjhU/v4+Hjt3bu31nuVlZVq165dnW0mT56s8ePH68wzz/RpH3a7XdHR0bU2MzHlBACAufwONMdq3769MjMz9Y9//EN33323T23S0tK0fv167+uysjK5XC7Fx8fX2eaNN97Q888/r9jYWMXGxmrt2rW68sorlZub25Tyg4YpJwAAzBWQQ+6ePXu893dqSGZmphwOh+bPn68xY8YoNzdXWVlZCgsLk9PpVPv27dW2bdtabX5+J+/rrrtOkydPbrb3j2LKCQAAc/l9yE1JSTlu3czu3bs1efJk33YYHq5Zs2Zp9OjRysnJUXV1tQoKCiS5z3iaMWOGRo4cWavNz0/TjoiI0Mknn6zY2Fh/yzcFU04AAJjL70CTn59f67XNZlO3bt3Uo0cPn39j5MiR2rp1qwoLC5WRkaGEhARJ7uknXzTnqwRLTDkBAGA2vw+5P7+79p49e9S5c2e/d5yUlKSkpCS/24UCz5QTIzQAAJjD70XBJSUlOuuss/TWW29JkoYOHaoBAwZoy5YtAS8uVDFCAwCAufwONBMmTNDFF1+sSy+9VJK0fv16ZWdna+LEiQEvLlSxKBgAAHP5fcjdtGmTFi5cqJiYGElShw4ddPvtt6t///4BLy5UsSgYAABz+T1CM3DgQL366qu13nv11Vc1YMCAgBUV6phyAgDAXH4fcl988UVdfvnlmjdvnrp3767S0lJVVFRo6dKlwagvJDHlBACAufw+5A4aNEhbt27VBx98oJ07d+qmm27S8OHDFRUVFYz6QhJTTgAAmKtRYwhRUVG6/vrrJblP2ybM1MaUEwAA5uK07SBgygkAAHNx2nYQMOUEAIC5OG07CJhyAgDAXJy2HQTc+gAAAHM1+bTt7777TgcOHOC07WMwQgMAgLmafNr2ddddp5iYGC1YsEBnnHFGMGoMOQQaAADM1ahD7rZt27R7926tXLlSa9as0dGjR5Wenh7o2kIWU04AAJjLp0Dz/fffa/ny5d6toqJCgwYN0saNG/Xyyy/r6quvVocOHYJda8hghAYAAHP5dMjt2rWrbDabLrzwQs2ZM0dZWVlq166d4uLilJmZSZj5GQINAADm8umQe+zozFVXXaXTTjtN6enpcrlc2rNnj0455ZRg1xkyDIMpJwAAzGYzDMPwp8G+fftqBZzy8nL16tVLQ4cO1V/+8pdg1dkkTqdTMTExcjgcio6ODuq+qqt/GpnZt0866aSg7g4AgBbLn+O335MinTp10vXXX++9l9PmzZv10Ucf6Z///Gfjqm1hPKMzElNOAACYxe8RmlBk5ghNVZXkWVJUWSl17BjU3QEA0GL5c/z2+0rBqJ9nQbDECA0AAGYh0ATYsVNOLAoGAMAcBJoAO3aEhkADAIA5CDQB5gk0bdq4NwAAEHwccgOMa9AAAGA+Ak2AcZVgAADMR6AJMAINAADmI9AEGFNOAACYL6QCTXl5udatW6fKykqrS6kTIzQAAJjPkkBTXFystLQ0xcXFKScnR75crPjZZ5/VgAEDNHHiRHXr1k0FBQUmVOo/Ag0AAOYzPdC4XC5lZ2dr8ODBKiwsVElJifLz8+tts2XLFj399NMqKSnRF198oXvuuUcPPfSQOQX7iSknAADMZ3qgWbJkiRwOh/Ly8tSzZ09NmzZNc+bMqbfN0aNHNXv2bHXp0kWSdMYZZ6iiosKMcv3GCA0AAOYz/bBbVFSk9PR0RUZGSpJSU1NVUlJSb5v+/furf//+kqSDBw/q+eef1zXXXBP0WhvDE2gYoQEAwDymj9A4nU6lpKR4X9tsNoWFhfk04vLhhx+qS5cu+v777/XAAw/U+T2XyyWn01lrM4tnyokRGgAAzGN6oAkPD5fdbq/1XkREhKqqqhpse+mll2rJkiUKDw/XH/7whzq/N336dMXExHi35OTkJtftK6acAAAwn+mBJj4+Xnv37q31XmVlpdq1a9dg2/DwcP3iF7/Qc889p7lz59b5vSlTpsjhcHi3HTt2NLluX7EoGAAA85keaNLS0rR+/Xrv67KyMrlcLsXHx9fZ5o033tCzzz7rfR0eHq6wehKD3W5XdHR0rc0sjNAAAGA+0wNNZmamHA6H5s+fL0nKzc1VVlaWwsLC5HQ6deTIkePa9O3bV4888ogWLVqksrIyPfzww/rlL39pduk+IdAAAGA+S9bQzJo1SxMnTlRiYqLefvtt5ebmSnKf8bR48eLj2px11lmaOXOm7rrrLg0aNEinnnqq8vLyzC7dJ0w5AQBgPpvhy2V6g2DXrl0qLCxURkaGEhISgrovp9OpmJgYORyOoE8/vfOONGqU9ItfSGvWBHVXAAC0aP4cvy2bGElKSlJSUpJVuw8appwAADBfSN2cMhQw5QQAgPkINAHGCA0AAOYj0AQYtz4AAMB8BJoA49YHAACYj0ATYEw5AQBgPgJNgDHlBACA+Qg0AcaUEwAA5iPQBBhTTgAAmI9AE2BchwYAAPMRaAKMERoAAMxHoAkwAg0AAOYj0AQYU04AAJiPQBNgjNAAAGA+Ak2AcR0aAADMR6AJMK5DAwCA+Qg0AcaUEwAA5iPQBBhTTgAAmI9AE2BMOQEAYD4CTYAx5QQAgPkINAHGlBMAAOYj0AQYU04AAJiPQBNgTDkBAGA+Ak2AMeUEAID5CDQBxpQTAADmI9AEGCM0AACYj0ATYIzQAABgPgJNgLEoGAAA8xFoAowpJwAAzEegCTCmnAAAMB+BJsCYcgIAwHyWBJri4mKlpaUpLi5OOTk5MgyjwTazZs1Sly5d1LZtW1166aXavXu3CZX6jyknAADMZ3qgcblcys7O1uDBg1VYWKiSkhLl5+fX22bt2rWaOnWqXn31VZWWlurw4cO65557zCnYT0w5AQBgPtMDzZIlS+RwOJSXl6eePXtq2rRpmjNnTr1tvv76a82cOVNZWVnq1q2bxo0bp8LCQpMq9g9TTgAAmM/0w25RUZHS09MVGRkpSUpNTVVJSUm9bcaPH1/r9ddff61evXrV+X2XyyWXy+V97XQ6m1Cxf5hyAgDAfKaP0DidTqWkpHhf22w2hYWFqaKiwqf2+/fv11//+ldNmjSpzu9Mnz5dMTEx3i05ObnJdfuKERoAAMxneqAJDw+X3W6v9V5ERISqqqp8aj9p0iRlZGRo+PDhdX5nypQpcjgc3m3Hjh1Nqtkf//2v+/FnfyIAAAgi08cR4uPjVVxcXOu9yspKtWvXrsG2r7zyilavXq1NmzbV+z273X5caDKLJ9D48OcAAIAAMX2EJi0tTevXr/e+Lisrk8vlUnx8fL3tPv30U02ePFkLFixQYmJisMtsNAINAADmMz3QZGZmyuFwaP78+ZKk3NxcZWVlKSwsTE6nU0eOHDmuzQ8//KDs7Gzde++9Gjx4sA4ePKiDBw+aXbpPCDQAAJjPkjU0s2bN0sSJE5WYmKi3335bubm5ktxnPC1evPi4Nm+++ab27NmjBx98UFFRUd6tOSLQAABgPpvhy2V6g2DXrl0qLCxURkaGEhISgrovp9OpmJgYORwORUdHB3Vfbdu6z3TauVNKSgrqrgAAaNH8OX5bdnJxUlKSklrYEb+m5qfTthmhAQDAPNycMoCOXf5DoAEAwDwEmgDyrJ+RCDQAAJiJQBNABBoAAKxBoAkgT6Bp04Z7OQEAYCYCTQBxyjYAANYg0AQQgQYAAGsQaAKIQAMAgDUINAFEoAEAwBoEmgAi0AAAYA0CTQB5LqxHoAEAwFwEmgBihAYAAGsQaAKIQAMAgDUINAFEoAEAwBoEmgAi0AAAYA0CTQARaAAAsAaBJoAINAAAWINAE0AEGgAArEGgCSACDQAA1iDQBBCBBgAAaxBoAohAAwCANQg0AUSgAQDAGgSaACLQAABgDQJNABFoAACwBoEmgAg0AABYg0ATQJ5AEx5ubR0AALQ2BJoAOnrU/di2rbV1AADQ2hBoAohAAwCANQg0AeQJNEw5AQBgLgJNABFoAACwhiWBpri4WGlpaYqLi1NOTo4Mw/Cp3TfffKP4+PggV9d4R464Hwk0AACYy/RA43K5lJ2drcGDB6uwsFAlJSXKz89vsF1paamGDx+uioqK4BfZSIzQAABgDdMDzZIlS+RwOJSXl6eePXtq2rRpmjNnToPthg8frptvvtmEChuPRcEAAFjD9EBTVFSk9PR0RUZGSpJSU1NVUlLSYLsPPvhAv/zlL33ah8vlktPprLWZgREaAACsYXqgcTqdSklJ8b622WwKCwtrcCqpR48ePu9j+vTpiomJ8W7JycmNrtcfBBoAAKxheqAJDw+X3W6v9V5ERISqqqoCto8pU6bI4XB4tx07dgTst+vDomAAAKxh+qE3Pj5excXFtd6rrKxUuwDeAMlutx8XmszACA0AANYwfYQmLS1N69ev974uKyuTy+Vq1qdj+4pFwQAAWMP0QJOZmSmHw6H58+dLknJzc5WVlaWwsDA5nU4d8czbhCBGaAAAsIYla2hmzZqliRMnKjExUW+//bZyc3Mluc94Wrx4sdklBQyBBgAAa1hy6B05cqS2bt2qwsJCZWRkKCEhQZJ7+qk+3bt39/mqwlZgUTAAANaw7NCblJSkpKQkq3YfFIzQAABgDW5OGUAEGgAArEGgCSDOcgIAwBoEmgBihAYAAGsQaAKIRcEAAFiDQBNAjNAAAGANAk0AEWgAALAGgSaAWBQMAIA1CDQBxAgNAADWINAEiGGwKBgAAKsQaAKkpuan5wQaAADMRaAJEM90k0SgAQDAbASaADk20LAoGAAAcxFoAoQRGgAArEOgCRDPgmCJQAMAgNkINAHiGaGx2aQ29CoAAKbi0BsgXIMGAADrEGgChKsEAwBgHQJNgDBCAwCAdQg0AcJVggEAsA6BJkAYoQEAwDoEmgAh0AAAYB0CTYCwKBgAAOsQaAKEERoAAKxDoAkQFgUDAGAdAk2AMEIDAIB1CDQBQqABAMA6BJoAYVEwAADWIdAECCM0AABYh0ATICwKBgDAOgSaAHE43I+RkdbWAQBAa2RJoCkuLlZaWpri4uKUk5MjwzAabFNQUKB+/fqpU6dOysvLM6FK/2ze7H7s08faOgAAaI1MDzQul0vZ2dkaPHiwCgsLVVJSovz8/Hrb7N27VyNGjND111+vTz75RK+//rpWrVplTsE+KilxP/bvb20dAAC0RqYHmiVLlsjhcCgvL089e/bUtGnTNGfOnHrbvP766+rSpYumTp2q3r1766GHHmqwjRl+/FHats29FRe73yPQAABgPtMDTVFRkdLT0xX5v8UmqampKvEMb9TT5uKLL5bNZpMknXPOOfr888/r/L7L5ZLT6ay1BcP770vdu7u37dvd7xFoAAAwn+mBxul0KiUlxfvaZrMpLCxMFRUVPreJjo7Wrl276vz+9OnTFRMT492Sk5MDU/zPhIVJERE/baNGSZ06BWVXAACgHqYHmvDwcNnt9lrvRUREqKqqyuc2DX1/ypQpcjgc3m3Hjh1NL/wEfvlL6dChn7a33grKbgAAQANMv2pKfHy8ij0LTv6nsrJS7dq1q7fN3r17ff6+3W4/LjQBAICWy/QRmrS0NK1fv977uqysTC6XS/Hx8T632bRpk5KSkoJaJwAACB2mB5rMzEw5HA7Nnz9fkpSbm6usrCyFhYXJ6XTqiOeSu8cYMWKE1q5dq1WrVuno0aN65plnNGzYMLNLBwAAzZTpU07h4eGaNWuWRo8erZycHFVXV6ugoECS+4ynGTNmaOTIkbXadOrUSc8++6yGDRummJgYdejQoVmctg0AAJoHm+HLZXqDYNeuXSosLFRGRoYSEhJ8avPNN99o8+bNuuCCCxQdHe3zvpxOp2JiYuRwOPxqBwAArOPP8duyQGMmAg0AAKHHn+M3N6cEAAAhj0ADAABCHoEGAACEPAINAAAIeQQaAAAQ8gg0AAAg5BFoAABAyCPQAACAkGf6rQ+s4Ll2oNPptLgSAADgK89x25drALeKQFNZWSlJSk5OtrgSAADgr8rKSsXExNT7nVZx64OamhqVl5crKipKNpstoL/tdDqVnJysHTt2cFuFBtBXvqOv/EN/+Y6+8h195btg9ZVhGKqsrFTXrl3Vpk39q2RaxQhNmzZt1K1bt6DuIzo6mn/hfURf+Y6+8g/95Tv6ynf0le+C0VcNjcx4sCgYAACEPAINAAAIeQSaJrLb7Xr44Ydlt9utLqXZo698R1/5h/7yHX3lO/rKd82hr1rFomAAANCyMUIDAABCHoEGAACEPAINgJCwf/9+rVu3Tvv27bO6FADNEIGmCYqLi5WWlqa4uDjl5OT4dGnmlm7//v1KSUlRWVmZ9736+qm19uF7772nHj16KDw8XEOGDNHmzZsl0Vd1WbBggXr16qXbbrtNp5xyihYsWCCJ/qrPZZddpvz8fEn0U11uv/122Ww279arVy9J9Fd97rvvPmVnZ3tfN6e+ItA0ksvlUnZ2tgYPHqzCwkKVlJR4/+PRWu3bt09XXnllrTBTXz+11j789ttvNW7cOOXm5mrXrl069dRTdfPNN9NXdThw4IBuv/12rVmzRhs3btRf//pX3XvvvfRXPV5//XV99NFHkvjfYH0+++wzLV68WBUVFaqoqNDGjRvpr3oUFxfrL3/5i2bMmCGpGf67ZaBRFi1aZMTFxRk//vijYRiGsWnTJuO8886zuCprDR061JgxY4YhySgtLTUMo/5+aq19+P777xszZ870vl65cqXRrl07+qoO27dvN1577TXv66KiIiMqKor+qsP+/fuNxMREo0+fPsbcuXPppzocOXLEiIqKMiorK2u9T3+dWE1NjZGRkWFMnTrV+15z6ytGaBqpqKhI6enpioyMlCSlpqaqpKTE4qqsNWvWLP3+97+v9V59/dRa+/DKK6/UxIkTva+//vpr9erVi76qQ3Jysm644QZJ0pEjR/TMM8/ommuuob/qcPfdd+vqq69Wenq6JP43WJcvvvhChmHozDPPVPv27XXZZZdp+/bt9FcdZs+erU2bNiklJUUffPCBjhw50uz6ikDTSE6nUykpKd7XNptNYWFhqqiosLAqa/Xo0eO49+rrJ/pQ+u9//6tnnnlGkyZNoq8aUFRUpMTERC1btkwzZsygv05g1apVWrFihZ588knve/TTiW3evFkDBgzQm2++qZKSErVt21YTJkygv07g4MGDevDBB9W7d2/t3LlTeXl5yszMbHZ9RaBppPDw8OOuiBgREaGqqiqLKmqe6usn+lB68MEH1bFjR91yyy30VQNSU1O1YsUKDRgwQOPGjaO/fubw4cOaMGGCZs6cWevmgPTTid1www1av3690tLSlJKSohdeeEHLli1TTU0N/fUz7777rn788UetXLlSU6dO1bJly3TgwAG98sorzaqvCDSNFB8fr71799Z6r7KyUu3atbOoouapvn5q7X24fPlyvfTSS3rjjTfUtm1b+qoBNptNgwYNUn5+vt577z3662cef/xxpaWlafjw4bXep598Exsbq5qaGp188sn018/s3LlTQ4YMUXx8vCR3SE5NTdXhw4ebVV8RaBopLS1N69ev974uKyuTy+Xy/gOHW3391Jr78LvvvtMNN9ygmTNnqn///pLoq7qsXLlSOTk53tfh4eGSpL59+9Jfx3jjjTf03nvvKTY2VrGxsXrjjTc0adIkzZs3j346gbvuuksLFy70vt6wYYPatGmjgQMH0l8/k5ycrEOHDtV6b9u2bXr22WebV18FdclxC3bkyBEjISHBmDdvnmEYhjFhwgTjyiuvtLiq5kHHnOVUXz+11j6sqqoy+vXrZ/y///f/jMrKSu/23//+l746gV27dhlRUVHGX//6V2P79u3GmDFjjGHDhvHv1s/s2LHDKC0t9W7XXnut8fTTTxt79+6ln05g3rx5Rq9evYyCggJjxYoVRt++fY3f/va3/Ht1Avv37zdiYmKMmTNnGjt27DD+/Oc/G3a73di6dWuz6isCTRMsWrTIaN++vdG5c2fjpJNOMoqLi60uqVk4NtAYRv391Br7cNGiRYak47bS0lL6qg5Lly41+vXrZ0RFRRmjRo0y9uzZYxgG/27V5ze/+Y0xd+5cwzDop7rcd999RmxsrJGcnGzccccdxsGDBw3DoL9O5JNPPjEyMjKM9u3bGykpKcaiRYsMw2hefcXdtpto165dKiwsVEZGhhISEqwup9mqr5/ow9roK//QX76hn/xDf/muufQVgQYAAIQ8FgUDAICQR6ABAAAhj0ADAABCHoEGAACEPAINAAAIeQQaAJb6+OOPZbPZam0dO3YMyr7y8/N14YUXBuW3AVgr3OoCACA6Olrbtm3zvrbZbBZWAyAUEWgAWM5msyk2NtbqMgCEMKacADRLjzzyiC6//HJdcMEFiomJ0XXXXSen0+n9fPXq1TrzzDMVFxen0aNH68CBA97PVqxYodTUVEVFRenyyy/Xzp07a/327NmzlZiYqM6dO+vtt982608CEEQEGgCWczgc3rtEx8bGasKECZKkpUuXavz48SosLFRZWZmmTp0qSdqxY4euuOIK3Xbbbfrss8908OBBjR07VpL7rr4jRozQXXfdpc2bNys2Nla/+93vvPv66quv9M4772jt2rUaO3as7rrrLtP/XgCBx60PAFjq448/1ogRI/TFF1943+vYsaNeeOEF/fOf/9TatWslSYsWLdKdd96psrIyTZ8+XatWrdKyZcskSeXl5UpKStLu3bv1yiuvaM2aNVqyZIkkaefOndq0aZOuvPJK5efn69Zbb1VZWZkSExO1ZcsW9enTR/xnEAh9rKEBYLk2bdqoe/fux72fnJzsfZ6UlKQffvhBknuEpkePHt7PunbtKrvdrh07dmjnzp21fqtbt27q1q2b93W/fv2UmJgoSWrXrl2A/xIAVmHKCUCzVVZW5n2+fft2denSRZJ0yimn6LvvvvN+tmvXLrlcLp1yyilKTk5WaWmp97MtW7Zo0KBBqqmpkeQ+owpAy0OgAWA5wzB04MCBWlt1dbXWr1+vefPmaevWrXrqqad0zTXXSJJuvPFGrVu3TrNnz1ZpaaluvfVWjRw5UomJibr++uu1Zs0a5efna8eOHXriiSfUuXNntWnDf+6Aloz/hQOwnNPpVFxcXK3tk08+UXZ2tubPn6+zzz5bPXv21MMPPyzJPY20ePFivfjiixo0aJA6dOiguXPnSpK6d++u9957T3l5eRowYIAOHDjg/QxAy8WiYADN0iOPPKKysjLl5+dbXQqAEMAIDQAACHmM0AAAgJDHCA0AAAh5BBoAABDyCDQAACDkEWgAAEDII9AAAICQR6ABAAAhj0ADAABCHoEGAACEPAINAAAIef8fVtBiIVyssDAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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DP+OP+ItiW0vP+lgQMh71nFwlrMx8MdAQERGZkb/v3sScA5tw91Gq2PZC2154rWN/WCkU0hVm5hhoiIiIzIBO0GFjzB/438l90Op0AAAXW3vM7TMW3Ro0lbg688dAQ0REJLHUrAzMj9yCP29dFtva1PXDgpDxqOPoImFlloOBhoiISELn7sRhzoFNeJChBgDIIMOEoN54tWMIrOQcYqooBhoiIiIJ6AQd1p2NwspTEdAK+UNMrrYO+LDfc+js20Ti6iwPAw0REZGJPcx6hA8PbsbJhKtiWzuvAMzvNw7uDs4SVma5GGiIiIhM6HTidXxw8CckZ6YDyB9ieqV9X7zSvh8UcrnE1VkuBhoiIiIT0Op0+OHMIXx/+iB0ggAAqG3vhHn9nkMH70YSV2f5GGiIiIiMTJWhxoeHNiM68brY1smnMeb2HYva9k4SVlZ9MNAQEREZ0V+3r+LDQ5uRkvUIACCXyfBqh1C81K435DIOMRkKAw0REZER5Om0WBV9AGvPHIaA/CEmD3tnzA8ZhyCvAImrq34YaIiIiAzs/qM0fHBwE87diRfbuvoG4oO+Y+Bq5yhdYdUYAw0REZEB/XnrMuYd2oy07EwAgEImx2udnsHzbXtyiMmIGGiIiIgMIE+rxben9uPHc1Fim6ejCxaEhKF13QYSVlYzMNAQERFV0d30VMw5sBF/37sltvVo0Axz+oyBi629hJXVHAw0REREVXAkPhbhkT9DrckCAFjJFZjceQDGte4BmUwmcXU1BwMNERFRJeRq87Dsr7346fxRsa2ekyvCQ8LQwtNXwspqJgYaIiIiPSWpH2J2xEbEPkgQ23r7t8Cs3qPhpLSTsLKai4GGiIhID5E3LmDh4a14lJMNALCWK/BWt8EY3aIrh5gkxEBDRERUATnaPHx1/FdsvXBcbPNxro3w0DA09fCWsDICGGiIiIjKdTtNhdkRm3BZlSi2hTRsjZm9RsLBxlbCyqgAAw0REVEZIq7F4KOo7cjM1QAAbBRWmNZ9KEY068QhJjPCQENERFSC7LxcfPnnHuyI/Utsq+/ijoWhYWjs7iVhZVQSBhoiIqIibqY+wKyIDbiWfFdsG9A4CO8Gj4C9tVLCyqg0DDRERERP+f3KWXxyZAey8nIAAEora/ynxzAMCezAISYzxkBDREQEIDs3B58f+wW7L0WLbf6udbAw9HkEuHlKWBlVBAMNERHVeHEP7+H9iA2IS7kvtg0JbI93egyHnbWNhJVRRTHQEBFRjSUIAn69fBqfHt0FTV4uAMDOygbvBo/AwCbtJK6O9MFAQ0RENVJmrgaf/rETv185K7Y1dKuLhaFh8HOtI2FlVBkMNEREVONcTb6D2REbcTP1gdg2olknvN19KGytrCWsjCqLgYaIiGoMQRCw6+JJfHFsNzTaPACAvbUNZvYahdBGbSSujqqCgYaIiGqEjJxsLD6yAxHXYsS2Ju5eCA8JQ/1a7hJWRoYgl+qDk5OT4e/vj/j4+ApdHxUVhWbNmsHd3R1LliwxbnFERFStXFYl4qWtXxcKM6NbdMXKEa8zzFQTkgQalUqFIUOGVDjMPHjwAMOGDcP48eNx/PhxbNiwAZGRkcYtkoiIRDqVCrnnz0OnUkldil4EQcDWC8cxaftyJKiTAQAONkosCn0e/+k5HErOl6k2JBlyGjduHMaNG4cTJ05U6PoNGzagXr16mDNnDmQyGT744AOsXr0affr0MXKlRETVk06lgjYpCQovL8jdy+6h0EREIHPZMkAQAJkM9pMnQxkaaqJKKy9dk4WPorbj0I2/xbZmHj4IDx0Pb+faElZGxiBJoFmxYgUCAgLw9ttvV+j6mJgY9O3bV9xyulOnTpg5c2ap12s0Gmg0GvG1Wq2uUr1ERNWJPgFFp1I9uRYABAGZy5fDOiio3CAkpdj7tzE7YhOS0h+KbeNadcfkLgNhreD00epIkiGngIAAva5Xq9Xw9/cXXzs7OyMxMbHU6z/66CO4uLiIX76+vpWulYioOiktoJQ2lKRNSnpyrfgmOmjv3DFypZUjCAJ+On8U/7fzWzHMONnY4pNnXsTb3YcyzFRjkk0K1oeVlRWUyienm9ra2iIzM7PU62fOnIm0tDTx6/bt26Yok4jI7OkbUBReXkDRAxnlcijq1TNShZWXlp2J/+5bj6V/7kGeTgsAaOlZH+vGTEWwfwuJqyNjs4io6ubmhgcPnmx+lJ6eDhub0s/WUCqVhQIQERHlEwPK06GmjIAid3eHTZ8+yDl0SGyz6d3b7IabLty7hdkRG3H3UarY9nybYLze6RlYKRTSFUYmYxE9NB07diw0gfjcuXPw9vaWsCIiIsskd3eH/eTJgPzxX/9yOezfeKPUgKJTqZBTZFVpzuHDZrPaSSfo8OO5KPx717dimHGxtcfnAydiStdBDDM1iFn10KjVatjZ2cHauvAyumHDhmHy5MmIjIxEz5498dlnn+GZZ56RqEoiIsumDA2FdVAQtHfuQFGvXpm9LWUNUUndS5OalYH5kVvw563LYlubun5YEDIedRxdJKyMpGBWgaZ169ZYunQpRowYUajd3d0dn3/+OZ555hm4uLjAwcEBq1evlqZIIqJqQO7uXqFAou8QlamcuxOHOQc24UFG/ipWGWSYENQbr3YMgZWcvTI1kUwQikZv83Xt2jVcvHgRvXr1grOzc4XvU6vVcHFxQVpaml73ERHR42Xey5cDOp04RCXVPjQ6QYd1Z6Ow8lQEtIIOAOBq64AP+z2Hzr5NJKmJjEef398WFWgqi4GGiKhqdCpVhYaojOlh1iPMO7gZfyVcFdvaeQVgXr9x8HDg3+3VkT6/v81qyImIiMxTRYeojOV04nXMPfgTVJnpAPKHmF5p3xevtO8Hhdwi1reQkTHQEBFZCH2OK6gutDodfjhzCN+fPgjd4wGF2vZOmNfvOXTwbiRxdWROGGiIiCyApZ6nVBXJmemYe/AnRCdeF9s6ejfCh/2eQ217JwkrI3PEQENEZOYs9TylqjiZcBVzD25GStYjAIBcJsOrHUIxIag3h5ioRAw0RERmzpz3gjG0PJ0Wq6IPYO2ZwxCQ/zN72Dtjfsg4BHnpdw4g1SwMNEREZs5c94IxtPuP0jD34E84eydObOvi2wRz+46Fq52jhJWRJWC/HRGRmdP3uAJL9Oety5iw9SsxzChkcrzReQCWDJrIMEMVwh4aIiILoM9xBZYkT6vFt6f248dzUWKbp6MLFoSEoXXdBhJWRpaGgYaIyEJIvReMod1NT8WcA5vw972bYluPBs0wp89ouNg6SFgZWSIGGiIiMrk/4mOxIPJnqDVZAACFXI7JnQdifOsekMlkEldHloiBhoiITCZXm4flf+3FpvNHxba6jrUQHhqGlp71JayMLB0DDRERmUSS+iFmH9iE2Pu3xbZe/i0wq/coOCvtJayMqgMGGiIiC1T0GARzPxYh8sYFLDy8FY9ysgEA1nIFpnQdhDEtu3GIiQyCgYaISEKVCSJFj0GwatMGeTExZnksQo42D18d/xVbLxwX27yd3bAwNAxNPXwkrIyqGwYaIiKJVOZ8ppKOQcg7d+7JBWZ0LMLtNBVmR2zCZVWi2NavYWvMDB4JR6WthJVRdcRAQ0QkAX3OZ3q6F6fEYxCKvbn0xyIcuHYei6K2ITNXAwCwUVjh7W5D8GzzzhxiIqNgoCEikkBFz2cq2otj+9JLxY9BKErCYxGy83Lx5Z97sCP2L7Gtvos7FoaGobG7lyQ1Uc3Aow+IiCQgns/0tCJBpKRenOx162BXEGpKIpNJdizCzdQHmLRjWaEw80zjtvhh1BSGGTI6BhoiIglU5Hym0npxFI0awemTT0p8X6dPPpFkQvDeK2cxcevXuJZ8FwCgtLLG+71G4cO+z8HBRmnyeqjm4ZATEZFEyjufqaxTtuXu7rDp2xc5hw6J37Lp2xdWTZqYqnwAQHZuDj4/9gt2X4oW2/xc62BhaBgautU1aS1Us7GHhojIhHQqFXLPn4dOpQKQ31Nj3apViUNEZfXi6FQq5ERGFro+5/Bh8X1NIe7hPbyyfVmhMDM4sD1+GPkmwwyZHHtoiIhMpDLLtEvrxanopGJj2XMpGp8d3YXsvFwAgK2VNd7tOQKDAtsb/bOJSsJAQ0RkYDqVCrkXL0Imk8GqaVOxR6Wiy7Sffp+C5drWrVoV+l5Zw1HGlJmrwWd/7MJvV86IbQ3dPBEe+jz8XesY9bOJysJAQ0RkQJqICGR+882Thsc9MXJPT716VMrrzSkYjspcvhzQ6UqcVGxo15LvYlbEBtxMfSC2DW/WCdO6D4WtlbXRPpeoIhhoiIgMRKdSFQ4zgNgT4/TxxxXuUalob07BcFTupUuQAbBq2tQIPxUgCAJ2XTyFL479Ao02DwBgb22D/waPxDON2xrlM4n0xUBDRGQg2qSkkr+h00HQaCrco6LP/Jjcs2f1npejj4wcDT4+sh37r8WIbY1r18PC0DDUr+VhsM8hqioGGiIiA1F4lbJ53OOeGOtWrcpcpl3ofSrQm1OZeTn6uKxKxKz9G5GgThbbRrXogre6DoaSQ0xkZrhsm4jIQOTu7rB/883Cu/gW2bm3rGXahd6nnE33gLJ7cqpCEARsvXAcr+74nxhmHGyUWBgahhk9RzDMkFliDw0RkQGVNK+lMr0l5W26BxhnpdMjTTYWRW3DoRt/i21NPbwRHhIGH5falX5fImNjoCGiau/p5c8FwaCkNkORu7tD2aNHpeoqpoxDKA290uni/QTMitiIpPSHYtvYlt3wZtdBsFHw1wWZN/4JJaJqraTlzwCMOpG2snU9XUNFN+GrSE9OeQRBwJa/j+HrE78jT6cFADjZ2GJ2nzHo5d+i8j8kkQnJBKGsM+irB7VaDRcXF6SlpcHZ2VnqcojIRHQqFdImTSo2JAOdrvCFcjlcVq402QnVpdVVUEN53zcktSYTCyO3Iio+VmxrUccXC0LGw8vZzaCfRaQvfX5/s4eGiKqt0ibNFmPCIwPKqqugBlMda3Dh3i3MjtiIu49SxbawNj3xeqdnYM0hJrIw/BNLRNVWaZNmS+qhMfaRARWpq6CGEpd/y2QGq1En6LAp5iiWn9wL7eNn4ay0xwd9x6BHg2YG+QwiU+OybSKqtkpb/mz/5pvlLomWoq5CNTy99NuA0rIzMOP3dfj6xG9imGldtwHWj3mLYYYsGntoiKhaK23SbFUn0hqrLqCUISlBqPKQ07k78fjgwCbcz0gT214K6o1XO4TCSqGo9PsSmQMGGiKq9uTu7sWCQEltplZaDYbeX0Yn6LD+bBRWnIqAVsjvlall64AP+z2HLr5NKvWeROaGgYaIyAwphw+HZteu/FBThWGxh1mPMP/QFpy4fUVsC6rnj/kh4+HhwFWfVH0w0BARGVBVN+wruv+McsQI2A4dWqn3OpN0Ax8c2ARVZjoAQAYZXm7fB6+07wcrOYeYqHphoCEiqoKnA0xVT74u6bBJzS+/wHboUL1q0up0WHPmEFafPgjd4/dys3PEh/2eQyefxnq9F5GlYKAhIqqkQr0pQOF5LxU8+frpQGSI/WeSM9Mx9+BPiE68LrZ18G6Eef2eQ217J71+PiJLwkBDRFQJxXpTAL3DSNHhJduXXqrSZOCTCVfx4cHNeJj1KP9WmQyTOoTgpaA+UMi5SwdVbww0RESVUGJvSlFlhJGShpey162D3UsvIWvdOr0Om8zTabE6+iDWnImEgPz3c7d3wvyQ8WjnFaD3z0ZkiRhoiIgqocSl1TJZ/lcFwkj27t0l9ugoGjWCy8qVFd4j5/6jNMw9+BPO3okT27r4NsEHfcfCzc6x0j+fMU8jJzIGBhoiokoo2O03c/nyQgGmIhv26VQqaHbuLOFN5eJ9FQkRx29dxrxDW5CanQEAUMjk+Hen/nihbTDkssoPMVX0pG8ic8JAQ0RUSaXt9lteGNEmJZX8fsOGVSjI5Gm1WBEdgXVnD4ttdRxcMD9kPNrW86tw/SUpaSisIpObiaTGQENEVAWV2XG4tOGqiizPvvcoFbMjNuHvezfFtu71m+KDvmPgYuugVx0lMdVJ30SGxmnvREQmVuLhlJMnlxsYjt68iBd//koMMwq5HFO6DsKnAycYJMwAT4WtQgWb9jRyospgDw0RkQTKOpyyqFxtHpb/tRebzh8V2+o61kJ4aBhaetY3aF2lzQ1i7wyZOwYaIiKJVGS4Kkn9EHMObMI/92+Lbb38mmNWn9FwVtobpS59whaRuWCgISIyU4fjLmBh5Fak52QDAKzkCkzpOghjW3aDrOiwkIGZw2nkRPpgoCEiMjM52jx8ffw3/HzhT7HN29kN4SFhaFbHR8LKiMwXAw0RkRlJSEvG7AMbcelBotjWN6AV3u81Co5KWwkrIzJvDDRERGbi4PXzWBS1DRk5GgCAjcIKU7sNwcjmnY0+xERk6RhoiIgkpsnLxZd//ortsSfENl8XdywMDUMTdy8JKyOyHJLsQ3PhwgV07NgRrq6umDFjBoRyDngTBAGffPIJGjduDHd3d0yePBkZGRkmqpaIyHhupT7ApB3LC4WZ/o3aYM2oKQwzRHoweaDRaDQYOnQo2rdvj+joaMTGxmLNmjVl3rN69Wp89dVX2LBhA44dO4aTJ0/itddeM03BRERGsu/qOUzc9jWuJt8BACgVVpjZayTm9RsHBxulxNURWRaZUF73iIHt3LkTr7zyChISEmBvb4+YmBhMnjwZR48eLfWe4OBgjBo1ClOnTgUA/Pbbbxg3bhzUanWFPlOtVsPFxQVpaWlwdnY2yM9BRFRZ2bk5WHJsN365dEpsa1DLAwtDn0ej2nUlrIzIvOjz+9vkc2hiYmLQpUsX2NvnbwjVunVrxMbGlnmPSqVC/fpPdsNUKBRQKBSlXq/RaKDRaMTXFQ0+RETGFpdyH7MjNuD6w3ti26Am7fCfnsNhb81eGaLKMvmQk1qthr+/v/haJpNBoVAgJSWl1Hvatm2LnTt3iq9/+OEH9O/fv9TrP/roI7i4uIhfvr6+BqmdiKgqfr18Gi9v+1oMM7ZW1pjdezQ+6DuWYYaoikzeQ2NlZQWlsvB/uLa2tsjMzISrq2uJ9yxatAgDBw5Ez549oVarcf78eRw5cqTUz5g5cyamT58uvlar1Qw1RCSZrNwcfPrHTvx25YzYFuDqiYWhYfB385SwMqLqw+SBxs3NDRcuXCjUlp6eDhsbm1Lv8fPzQ2xsLC5duoR3330Xnp6e6NmzZ6nXK5XKYqGJiEgK15LvYlbEBtxMfSC2DW3aAe90HwZb69L/3iMi/Zg80HTs2BGrVq0SX8fHx0Oj0cDNza3M+2QyGZydnXHgwAEcO3bM2GUSEVWJIAj45dIpLDn6CzTaPACAnZUN/hv8LAY0CZK4OqLqx+RzaIKDg5GWloZ169YBABYvXoyQkBAoFAqo1Wrk5uaWem94eDjGjBmDdu3amapcIiK9ZeRoMPfgZnwUtV0MM41r18Pa0VMYZoiMRJI5NCtWrEBYWBhmzJgBrVaLqKgoAPkrnpYuXYoRI0YUu+/atWvYuHFjseEqIiJzckWVhFkRG3E7TSW2Pdu8M6Z2GwJbK2sJKyOq3ky+D02BxMREREdHo1u3bvDw8DDqZ3EfGiIyNu2DB9h29gi+iT+DHJ0WAGBvrcT7vUYhpFFriasjskxmvQ9NAW9vb3h7e0v18UREBpO893csPr4bf9R78hduoLs3FoaGwceltoSVEdUces+huXLlijHqICKySP9cuYB/xUYUCjPDbqbgu55jGGaITEjvQNOmTRu0a9cOH3/8MeLi4oxRExGR2RMEAZv/PoZ/R27EXfv85dcOuVrMPpOA12PvQnH/QTnvQESGpHegUalUeP/99/H333+jffv26Ny5M7744gskJCQYoz4iIrOj1mTivf0/4otju5En6AAAgalZ+OZYHLrfSwfkcijq1ZO4SqKaRe9A4+DggNGjR+PHH3/E/fv3MWnSJMyfPx9+fn4IDg7Gn3/+aYw6iYjMwoV7tzDh568QFfeP2DbWpT4+PXkLdbNyAbkc9m+8Abm7u4RVEtU8lZoUfPXqVWzbtg3bt2/HP//8g4EDB+K5555DZmYmRo8ejaSkJEPXSUQkKUEQsPH8H1j+115odfm9Ms5KO8zpMwY9/ZpDFzoW2jt3oKhXj2GGSAJ6B5pWrVrh+vXreOaZZzBt2jQMGzYMDg4OAIC4uDijL8EmIjK1tOwMzI/8GcduXhLbWnk2wIKQ8ajrVAsAIHd3Z5AhkpDegea///0vhg8fDicnp2Lf8/f3R0xMjEEKIyIyBzF34vHBwU249yhNbHuxbS/8u2N/WCkUElZGRE/TO9C88MILhV7fv38fderUMVhBRETmQCfo8OO5I/ju5H5oH0/8rWXrgLl9x6Jr/UCJqyOiovSeFBwbG4t27drh559/BgD069cPLVq04P40RFRtpGQ9wvTf1uTPl3kcZoLq+WPd6LcYZojMlN6B5t///jf69u2L/v37AwBOnDiBoUOH4rXXXjN4cURkvnQqFXLPn4dOpSr/YgtyJukGJvz8FU7czv+fNBlkeLldX3w9dBLqOLpIXB0RlUbvs5ycnJxw5coV1Htqj4XExEQ0b94caWlpZdwpHZ7lRGRYmogIZC5bBggCIJPBfvJkKENDpS6rSrQ6HdaejcSq6APQPf5r0dXOEfP6PYdOPo0lro6oZtLn97fePTStWrXC+vXrC7WtX78eLVq00PetiMgC6VSqJ2EGAAQBmcuXW3RPTXJmOqb++j1WnIoQw0wH74ZYP/othhkiC6H3pOBly5Zh4MCBWLt2Lfz8/BAXF4eUlBTs3bvXGPURkZnRJiU9CTMFdDpo79yxyGXLpxKuYe7Bn/Aw6xEAQC6T4V/t+2Fiu75QyPX+fz4ikojegSYoKAhXr17F7t27kZiYiBdffBGDBw8ucRk3EVU/Ci8vQCYrHGoscKt/rU6H708fxPenD0FA/s/ibu+Eef3Gob13Q4mrIyJ9VWqnYCcnJ4SFhRVqe/DgATfVI6oB5O7usJ88GZnLlwM6nUVu9f8gQ40PDmzC2TtPDtjt7NMYc/s9Bzc7RwkrI6LK0jvQxMbGYsaMGbhy5Qq0Wi2A/C3Bk5KSoNFoDF4gEZkfZWgorIOCLHKr/xO3r2Dewc1Iyc4AAChkcvxfx1C8GNQLchmHmIgsld6B5uWXX0bXrl1Rt25dqNVqvPLKK5g+fToWL15sjPqIyExZ2lb/eTotVpyKwLqzh8U2DwdnLAgJQ9t6fpLVRUSGoXeguXDhAnbv3o24uDhMmTIFAwcOhLOzM9544w1MmzbNGDUSEVXJvUepmHNgE87fvSm2da/fFHP6jEEtOwcJKyMiQ9E70DRp0gTff/893n77bVy/fh0qlQp16tRBXFxc+TcTEZnYsZuXMO/QFqg1mQAAhVyONzoNwPg2PTjERFSN6B1ovvrqK4wZMwavvPIK/vWvfyEgIAAymQzDhw83Rn1ERJWSp9Vi+cm92Bjzh9hW17EWwkPD0NKzvoSVEZEx6L1TMJA/CRgAZDIZoqKi8OjRIwwYMAAKMz15ljsFE9UsSeqHmHNgE/65f1tsC/Zrjlm9R8PF1l7CyohIH/r8/q7Usm2ZTCb+c69evSrzFkRERhEV9w/CI39Gek42AMBKrsCULgMxtlX3Qn93EVH1ovcA8vLly5GUlGSMWoiIKi1Hm4cvju3Gf/etF8OMl5MbVox4Dc+17sEwQ1TNVWoOTUBAALy8vIxRDxGR3hLVyZgVsRGXHiSKbX0DWuH9XqPgqLSVsDIiMhW9A82cOXMQHh6OHj16wNGRO2oSkbQOXf8bC6O2IiMnf2NPa7kCU7sNwagWXdgrQ1SD6B1orl27Bp1Oh8aNG2PChAlwcHiyh8MHH3xg0OKIiEqjycvFV8d/xbZ/TohtPs61sbB/GALdvSWsjIikoHegiY+PR2BgIAIDA3H//n1j1EREVKZbqSrMjtiAK8l3xLb+jdrgv8Ej4WCjlLAyIpKK3oHmhx9+MEYdREQVsv/qOSw+sh2ZuTkAAKXCCtO6D8PwZh05xERUg+kdaG7dulXq9+rX52ZVRGQc2Xm5+OLYbuy6eFJsa1DLA+GhYWhcu56ElRGROdA70Pj5+UEmkxXaXK9AwenbRESGFJ9yH7MiNuD6w3ti28AmQZjRcwTsrTnERESV2IdGp9NBq9VCp9MhIyMDkZGR6N27Nw4ePGiM+oiohvvt8mlM3Pa1GGaUVtaY3Xs05vZ9jmGGiESVOvqgqIyMDAQHB+P06dOGqMngePQBkeXJys3BZ0d34dfLT/5eCXD1xMLQMPi7eUpYGRGZitGPPijq/v37uHPnTvkXEhFVwPWHdzErYiPiU56spBzatAPe6T4MttY2ElZGROZK70Dj7+9fbN7MnTt38PbbbxuyLiKqgQRBwO5L0fj82C/Q5OUCAOysbPDf4GcxoEmQxNURkTnTO9CsWbOm0GuZTAYfHx8EBAQYqiYiqoEycjT45I8d2Hf1nNjWqHZdLAx9Hg1qeUhXGBFZBL0DTdHTte/fv486deoYrCAisiw6lQrapCQovLwgd3ev1HtcVSVhVsRG3EpTiW3PNu+Mqd2GwNbK2lClElE1pvcqp9jYWLRr1w4///wzAKBfv35o0aIFrly5YvDiiMh4dCoVcs+fh06lKv/iUmgiIpA2aRIezZmDtEmToImI0Ot+QRCw/Z8T+NeO5WKYsbdWYkHIePw3+FmGGSKqML17aP7973+jb9++6N+/PwDgxIkTWLBgAV577TUcOnTI4AUSkeFpIiKQuWwZIAiATAb7yZOhDA3V6z10KtWT9wAAQUDm8uWwDgqqUE9NRk42FkVtx8Hr58W2QHdvhIeOh69L5Xp6iKjm0jvQnDt3Dlu2bIGLiwsAwMHBAVOmTEHz5s0NXhwRGZZOpULuxYtVCiIFtElJT95D/AAdtHfulPs+lx4kYHbEJiSok8W2MS27YUrXQbBRGGTxJRHVMHr/zdGqVSusX78e7777rti2fv16tGjRwqCFEZFhFeqVKaqCQeRpCi8vQCYr/H4yGRT1Sj+GQBAE/HzhT3x9/Dfk6vJ3Fne0scWs3qPRJ6BlhT+biKgovQPNsmXLMHDgQKxduxZ+fn6Ii4tDSkoK9u7da4z6iMgAig0PFSWXlxlESrzF3R32kycXe9/cs2dLHL5K12Rh4eGtOBz3j9jW3MMH4aFh8HJ20+uziYiK0jvQBAUF4erVq9izZw8SEhLw4osvYvDgwXBycjJGfURkACUODxWQy2H/xhuVWqFkHVRkb5hShq/+uXcbsw9sxJ30FLFtfOseeKPzAFhziImIDKBSf5M4OTlh/PjxAPKXbTPMEJm30oaHHP7zH1g1bVrp5dblzaMRBAGbzh/Fsr9+h1anAwA4K+0wp88Y9PTjvDsiMhwu2yaqAQqGhyB//J+8XA77yZNh06NHpcMM8FRQKvRh+cNXadmZmLF3Hb46/qsYZlp51se60VMZZojI4PQ+nLJnz57o3Lkz5syZAxcXF2RkZGDBggU4efKk2S7b5uGURPl0KhW0d+5AUa9elYLM0zQREchcvhzQ6cThq8utmmDOgY249yhNvO6Ftr3wWsf+sFIoDPK5lsAQmw4S1WT6/P7WO9A4OTnhypUrqPfUBMLExEQ0b94caWlpZdwpHQYaIuMqCEqyunWxMeEffHdyP7RCfq9MLVsHfNB3LLrVD5S4StMyxF4/RDWdPr+/9R5yKli2/TQu2yaq2eTu7njUyB8zTu7B8r/2imGmbT0/rBv9Vo0LM6VtOliVXZmJqGxVXrZ948YNpKamctk2UQ12NukGPjjwEx5kqgEAMsgwsV0f/KtDP1jJa84QU4GqbDpIRJVT5WXb48aNg4uLC3766Se0adPGGDUSkZnS6nRYezYSq6IPQPf4F7irnSM+7PscOvs2lrg66ZS4qqwSe/0QUcVVatn2zZs3cefOHRw6dAh//PEH8vLy0KVLF0PXRkRmLDkzHR8e3IxTidfEtvZeAZjXbxzcHWr2XDVx08Eik6XZO0NkPBUKNHfv3kVERIT4lZKSgqCgIJw9exarVq3Cs88+CwcHB2PXSkRmIjrxGuYe3IzkzHQAgFwmw7/a98PEdn2hkOs9Na9aUoaGwjooyOCryoioZBUKNF5eXpDJZOjduzdWr16NkJAQ2NjYwNXVFcHBwQwzRDWEVqfD96cP4vvThyAgfziltr0T5vcbh/beDSWuzvzI3d0ZZIhMpEKB5unemeHDh6NJkybo0qULNBoN7t+/j/r16xu7TiKS2IMMNeYe/Alnkm6IbZ19GmNuv+fgZucoYWVERJXYh0alUhUKOElJSWjUqBH69euH5cuXG6vOKuE+NGTJzGFztr9uX8GHBzcjJTsDQP4Q0/917I8JQb0gl3GIiYiMw6gb6xV18eJF7Nu3DwcOHMCePXuq8lZGw0BDlkrqzdnydFqsPHUA684eFoeYPBycsSBkPNrW8zdZHURUMxl1Y72imjVrhrfffluvMHPhwgV07NgRrq6umDFjBiqSqT799FN4enrC2dkZo0aNQnJyclXKJjJ7Um/Odv9RGib/shJrz0aKYaZb/UCsHz2VYYaIzI7J+4o1Gg2GDh2K9u3bIzo6GrGxsVizZk2Z9xw5cgRr167FkSNHcObMGWRnZ+Odd94xTcFEEilrc7ZCTSoVcs+fN2jQ+fPmJby49UvE3I0HAChkckzpMgifDXwJtey4CICIzE+l9qGpit9//x1paWlYsmQJ7O3tsWjRIkyePBkvv/xyqfecPHkSgwYNQmBg/vbp48ePN9v5OkSGUpHN2Qw9JJWn1eJ/J/dhQ8wRsa1OVi7ei0lE+wAN58sQkdky+d9OMTEx6NKlC+zt7QEArVu3RmxsbJn3tGzZEtu3b8f169dx//59rF69GqE85I2quYLN2VCwr0uRzdkMPSR1Jz0Fr/3yXaEw0+VeOr45dgPNUrLM6iwiY/RKEZFlM3kPjVqthr//k/F3mUwGhUKBlJQUuLq6lnjPgAED0LhxYzRq1AgA0LFjR7z33nulfoZGo4FGoyn0mUSWqKzN2Qx5XtCRuH8Qfngr1JosAICVTI5//ZOE4TdTIKviexua1BOlicg8mbyHxsrKCkqlslCbra0tMjMzS71ny5YtuHnzJi5duoTk5GS0bNkSL7zwQqnXf/TRR3BxcRG/fH19DVY/kanJ3d1h3apVsSAhDkkVuli/84JytXn44thuvLtvvRhmvJzc8G2f8RhxKxWF3t0MziKSeqI0EZkvkwcaNzc3PHjwoFBbeno6bGxsSr1n06ZNeP311xEYGAg3NzcsXboU27dvR2pqaonXz5w5E2lpaeLX7du3DfkjEJmF8oakypOoTsb/7fwWm/8+Jrb1CWiJtaOnoGWTVlV6b2Op6ERpIqp5TD7k1LFjR6xatUp8HR8fD41GAzc3t1LvycvLw71798TXdx7/5aXVaku8XqlUFusFIqoqc9jgrqjKnhd06MbfWHh4KzJy8odmreUKTO02BKNadIHsca+POZ5FxFOsiag0Jg80wcHBSEtLw7p16zBhwgQsXrwYISEhUCgUUKvVsLOzg7W1daF7unfvjiVLlsDHxwd2dnZYunQpunbtitq1a5u6fKqhzHneRkHQ0CYlFXpdEk1eLr4+/hu2/nNcbPNxro2F/cMQ6O5d4nubQ5ApwFOsiag0Vd4puDJ27tyJsLAwODk5QavVIioqCi1atICfnx+WLl2KESNGFLo+Ozsb7777LrZt2waVSoWuXbti9erVaNiwYofhcadgqgqdSoW0SZOK9Qq4rFxpFr9IKxq2bqWqMPvARlxRJYltoY3a4L3gZ+FgY2vKkqtMp1KZVc8RERmHSY8+qKzExERER0ejW7du8PDwMOpnMdBQVeSeP49Hc+YUa3cMD4d1q1YG+YyyhrPK+15FwlbEtRh8dHgbMvNyAABKhRWmdR+K4c06iUNMRETmRp/f3yYfcirg7e0Nb+/iXdxE5sbY8zZK62HRqVTI3r0bml27xM+2eeYZ2I0dW3iYqYRJsrmXLkHZowey83Kx9Nhu7Lx4Uvy2zyMN5jfthObNOxukfiIicyBZoCGyFMact1HqMuRHj5BdwpEgOfv2IWffPti/+SaUoaGQ2doWD1sAMj/7DDfTVJiXEY/rD++K7f0SUzH5n7uwOxYPXZdgDtcQUbXBQENUAcZa8VNaD0tJYeZpmcuW5YeetWuL3w/gYD0nfBP3J7Kt8pddK7U6vPHPXYQmpj3eW0Ywi03yiIgMhYGGqIKMseKnxOGsEnpcihGEEkNPtkKG5c3rIsKnltjm71wb//31FBo8erJ7Npc6E1F1w5PmiCRU0uZ4di+9VHwH4Aq46WiDqV39C4WZIX4t8cOYqWg28VWz2ySPiMiQ2ENDJLGShrNkjo5P5uwUJZPB7qWXkPV4uEkAsN/HBf9rXhcaRX5osc3T4R2vlhg64PERIQYeMjPHTQaJqGZjoCEyA0WHs4qGHADIu3QJAgDrpk3F0JP83f/wTTNPHPJ2Ee8NkCkRPigMAQGBZX5GZZnzJoNEVHMx0BAZUVV6MooGEJsePQp9/1a7lnh/WAfcznxymvygWyn4v8sP4Nr8PnTOtSF3dzdob0ppq7Ksg4LYU0NEkmKgITISY/VkCIKAnRdP4otju5GjzQMA2OVp8daFu+h9Jz/cZH72GSCTwaZPH+RERhqshrIOh2SgISIpMdAQGUFpPRmwtYV1s2Z6/fJ/uocly9kRH0Vtx4Hr58XvN0zLxvvnEuCVmVv4RkFAzqFDhV5XtTeFh0MSkblioCEygtJ6Mgp6TiraU5K1Y4e4PPuaiy0W92qOxNws8ftD4x9i0uX7sNFV8ASTKvam8HBIIjJXDDRERqDw8ir9mxXsKcl+HGYEALvru2JlszrIexxmHG1s8a5nC3T8/Uf9CjNAb4qxNhkkIqoK7kNDZAS5Z8+WvZfM456SUr+tUiFr7Vo8spJjYZA3/teiLvIe7yPTzLE21o1+CyGd+5T8GQVtcjls+vY1yv4zcnd3WLdqxTBDRGaDPTREBlZs/kxJyukp0SYl4bKzEh+19cY9exux/dn4h3h7+jQond0AoMThn6K9J3bPP8/eFCKq9hhoiAysxPkzwJPJtOX0lAiCgJ8fJWF5Fz/kyfN7WxxztHjn7yT0HjQayjqe4rXWQUGwnz4dMpkMVo/3pwFQ6L2NcWQDEZG5YaAhMrDSVgI5ffwxBI2mzJ6StOxMhB/+GX/EXwQeh5lmKZn4b0wS/J57HrbPPiteyw3uiIieYKAhMrDSVgJZNWkCIH9IKvf8+WIb3f199yZmH9iIe4/SxLbnm3TEpNqNoHzVu9C13OCOiKgwBhoiIyhtJVBJvSrWIf2w4dwf+PbkPmiF/LObXGztMbfPWHRr0LTE9+cGd0REhTHQED1m6AMXi85dKalX5c7K7/Blxg0cvxsnXtemrh8WhIxHHUeXom8p4gZ3RESFMdBQjVYQYrTXr4unVxtrPkrRXpULrnZY3NYbyY/DjAwyvNSuNyZ1CIGVXFHme3GDOyKiwhhoqMYqNPzzNCPNRynoVdEJAjY3rI0fG3tA93jPGFdbB3zYbxw6+zbOn2NTgZ4ibnBHRPQEAw3VSOXuFWOE+Shyd3dk/3sS5p/eh7PuDmJ7e68AzOs3Du4OzmWuXCppSIxLsomI8jHQUI1U6l4xBYwwHyU68RrmPohB8uMwIwPwrw4heLldXyjk8jJXLuWePcsl2kREZWCgoRqpxEm1BQw8H0Wr0+H70wfx/elDEJD/ebXtnTC/3zi092745LpSVi7lnDqFrG+/fdLGJdpERMUw0FCNVNKkWtsJE2DVqJFB56OoMtSYe/AnnE66IbZ18mmMuX3HwjVTU2g/mhJDlkxWOMwU4BJtIqJCGGioxjL2pNq/bl/Fh4c2IyXrEQBALpPh/zr2x4SgXsg9cBBpJQwhFQ1Z0OlKfnMu0SYiKoSBhmo0Y0yqzdNpsSr6ANaeOSwOMXk4OGNByHi0redf5lyZp0OWLjUVmZ99VvwDZDIu0SYiKoKBhsiA7j9KwwcHN+HcnXixratvIOb2HYtadvmTgcvb5bfgS6dSlTgE5fTJJ+IxCkRElE8udQFE1cWfNy/hxa1fimFGIZPjzS4D8fmgl8QwAzw1IflpJQwhFczzgVwuXmM/eTLDDBFRCdhDQxbP0EcW6CtPq8X/Tu7DhpgjYpunowvCQ8LQqm6DYtfrs8svN88jIqoYBhqyaGVtRGcKd9NTMefARvx975bY1tOvGWb3HgMXW/tS79MnqHDzPCKi8jHQkMUqa3KtKQLAkfhYhEf+DLUmCwBgJVdgcucBGNe6B2RFh5RKwKBCRGQ4DDRkscqbXGtoBUNburqe+N+1U/jp/FHxe/WcXBEeEoYWnr4G/1wiIiofAw1ZrBI3ojPS/iwFQ1t3ba3wUVtvXKllJ36vt38LzOo9Gk5KuzLegYiIjImBhiyWPpNrK0unUiH34kVkLluGY3Uc8UWresiwVgAArOUKTO02BKNadKnQEBMRERkPAw1ZNGOuAirolcmRAaua1sFuPzfxe/UycrCg23C0bNnVYJ9HRESVx0BDFs8Yk2sLJhwn2VlhUVsfXHexFb8XnJSGt/65i9oBDw36mUREVHkMNEQl0CYlIcrTEV+2qocsq8dDTFodXrt4DwNvp0IGIHvdOih79uRKJSIiM8BAQ2ZLqg3zsvNy8UX8aewK8hHbvB9pMOtcIvzTNU8VWLkVVVJvBEhEVB0x0JBZkmrDvJupDzArYgOuJd8V2/ompuHNf+7ATltkiXglVlRJvREgEVF1xbOcSFI6lQq558/nH8T4VFtJG+Y9fY0x/H7lLCZu/VoMM0qtDm//nYT/nE/KDzMy2ZMzmCqxokqqn4uIqCZgDw1JprTeClNvmJedm4PPj/2C3ZeixTZ/1zqY6+gPzwPr8hseB5iqrKgy9c9FRFSTMNCQJMo6tsCUG+bFPbyH9yM2IC7lvtg2JLA93ukxHHbWNtB17lkswFQ2fJjy5yIiqmk45ESSKK+3wn7yZED++I9nJYd3nh7KKvpaEATsuRSNidu/EcOMnZUN5vYdi9l9xsDO2ib/o93dYd2qlUF6UAzxcxERUcnYQ0OSKK+3oiob5hUdyrLp0wc5kZHia7z+b3xlrcbvV86K9zR0q4uFoWHwc61jsJ+xJMbcCJCIqCaTCULR/02uftRqNVxcXJCWlgZnZ2epy6HHNBERxY4tqOqKH51KhbRJk4r3/jwW56TEorbeSHBUim0jmnXC292HwtbKukqfbWpc/k1E1Z0+v7/ZQ0OSMUZvRYlDWQAEAL/71sJ3zTyRo8gf8rG3tsHMXqMQ2qhNlT/X1Lj8m4ioMAYakpShjy0oaSgrw0qOr1vURZSXi9jWpFYdhA+YgPq1LK9no6wJ1eypIaKaipOCqVopOvH2mosdpvZrXijMPOvsg5Wjp1hkmAHKnlBNRFRTsYeGqh1laCis2rbF1rNR+Cb+LHJ1WgCAg8IaMzsOQEjb7hJXWDVc/k1EVBx7aKjaSddkYc7Z/fjiRrQYZpp5+GDdc29bfJgBuPybiKgk7KGhaiX2/m3MjtiEpPSHYtu4Vt0xuctAWCss5497eSuYuPybiKgwy/kbnqgMgiBg89/H8M2J35H3uFfGycYWc/qMQbB/C6N8prGWTVd0BZOhJ1QTEVkyBhqyeGnZmVh4eCuOxMeKbS0962NByHjUc3I1ymcaa9k0VzAREVUOAw1ZtAv3bmF2xEbcfZQqtj3fJhivd3oGVgqFUT7TmKGDB1gSEVUOAw2ZlYoO4+gEHTbG/IH/ndwHrU4HAHCxtccHfcaie4OmRq3RmKGDK5iIiCqHgYbMRkWHcVKzMjA/cgv+vHVZbGtT1w8LQsajjqNLsesNzZiho2AFU9EjIdg7Q0RUNkmWbV+4cAEdO3aEq6srZsyYgfKOk/rwww8hk8mKfR0+fNg0BZPRlTaMU3A6doFzd+Lw4tYvxTAjgwwvBfXBsmGvmiTMAMZfNq0MDYXLypVwDA+Hy8qVPNKAiKgCTB5oNBoNhg4divbt2yM6OhqxsbFYs2ZNmfe89957SElJEb9iYmLg4eGBoKAg0xRNRlfe7rc6QYc1ZyIx+ZeVeJChBgC42jpg6eCX8XrnZ2AlN858mdJUNnToVCrknj9fLKgVJXd3h3WrVuyZISKqIJMPOf3+++9IS0vDkiVLYG9vj0WLFmHy5Ml4+eWXS73H1tYWtra24ut3330X06ZNg4uLaf6PnIyvrGGch1mPMO/gZvyVcFX8VjuvAMzrNw4eDmWfvmrME6n1XTbNAyWJiIzH5IEmJiYGXbp0gb29PQCgdevWiI2NLeeuJ5KSkrBjxw7ExcWVeo1Go4FGoxFfq9XqyhdMJlHa3JGzmjTM/e07qDLTAeQPMb3Svi9ead8PCnnZHYzmFCC4HJuIyLhMHmjUajX8/f3F1zKZDAqFAikpKXB1LX/PkG+//RZhYWFwdHQs9ZqPPvoI8+bNM0i9ZDpP736Lup5Ye/M8vt+zCrrHIcDNzhHzQ8ahg3ejct/L3AIEl2MTERmXyefQWFlZQalUFmqztbVFZmZmufdqtVqsXLkSr732WpnXzZw5E2lpaeLX7du3q1QzmY7c3R3qhn6YdmIXVkUfEMNMR+9GWD9maoXCDGB+J1KLQ2pP43JsIiKDMXkPjZubGy5cuFCoLT09HTY2NuXeGxkZCXd3dzRr1qzM65RKZbHQRJbhZMJVzD24GSlZjwAAcpkMr3YIxYSg3uUOMT3N3PZz4XJsIiLjMnmg6dixI1atWiW+jo+Ph0ajgZubW7n3btmyBc8++6wxyyMJ6FQqaBITsCYlHusu/QUB+SHEw94Z80PGIcgrQO/3NMcAwQMliYiMx+SBJjg4GGlpaVi3bh0mTJiAxYsXIyQkBAqFAmq1GnZ2drC2ti7x3r1792Lt2rUmrpiMSRMRgVurvsPHbbxwwc1ebO/i2wRz+46Fq13pc6XKY44BggdKEhEZh0wob1c7I9i5cyfCwsLg5OQErVaLqKgotGjRAn5+fli6dClGjBhR7J7r168jMDAQqampZU4ILolarYaLiwvS0tLg7Fz2Ml8yHZ1KhQPvTcVnretBbZOfreU6Aa+16YUXug2AXCbJvo9ERGQm9Pn9LcnRByNGjMDVq1cRHR2Nbt26wcPDA0D+8FNpGjZsiLy8PBNVSMaWp9Vi+Z+/YmMHX7HNIysX751LRKeevgwzRESkF8nOcvL29oa3t7dUH08SupueijkHNuHvezfFts730jH97ztw1gplTtw15kZ5RERkuXg4JZnUH/GxWBD5M9SaLACAQifgX5fvY0T8Q8gA2E6cWGpQMaeN8oiIyLww0JBJ5GrzsPyvvdh0/qjY5pmZg5nnEhGYli22WTUqeZ8Zc9soj4iIzAsDDRldkvohZh/YhNj7TzY47OXVGG+u+xWOudonF5axTwx32iUiorIw0JBRRd64gIWHt+JRTn4vjLVcgbe6DcboFl2RY1e/QvvE6FQqCCWdx8WddomI6DEGGjKKHG0evjr+K7ZeOC62+TjXRnjoeDT18AFQsX1iis6bAZD/z2awUR4REZkPBhoyuNtpKsyO2ITLqkSxrV/D1pgZPBKOSttC15a10VxJ82Ygl8P+P/+BddOmZhNmuPKKiEh6DDRkUAeunceiqG3IzNUAAGwUVpjWfShGNOsEWdHDGctR2rwZuYtLseBQ1VBR2fu58oqIyDww0JBBZOfl4ss/92BH7F9iW30XdywMDUNjd69KvWdFD5isaqio7P1ceUVEZD64HStV2c3UB5i0Y1mhMPNM47b4YdSUSocZ4MkBkyg4ZbuEeTOlhQqdSlWhz6jK/WWtvCIiItNiDw1Vyd4rZ/HxkR3IyssBACitrPGfHsMwJLCD3kNMJSlv4nBVl3NX5f6K9iAREZHxMdBQpWTn5uDzY79g96Vosc3PtQ4WhoahoVtdg35WWROHqxoqqnJ/QQ9SRZaeExGRcTHQkN7iHt7DrIiNuJFyT2wbHNge/+kxHHbWNiatpaqhoqr3V2TpORERGZ9MEIr2t1c/+hw/TmXbcykanx7dBU1eLgDA1soa7/YcgUGB7SWtS6dSVSlUVPV+IiIyPH1+f7OHhiokM1eDz/7Yhd+unBHbGrp5YmHo8/BzrSNhZfnKGpYyxf1ERCQtBhoq17Xku5gVsQE3Ux+IbcObdcK07kNha2UtYWVERET5GGioVIIgYNfFU/ji2C/QaPMAAPbWNngveCT6N24rbXFERERPYaChEmXkZGPxkR2IuBYjtjWpXQ/hoWGoX8tDwsqIiIiKY6ChYi6rEjFr/0YkqJPFtlEtuuCtroOh5BATERGZIQYaEgmCgG3/nMCXf+5Brk4LAHCwUWJWr9Ho27CVxNURERGVjoGGAACPNNlYFLUNh278LbY18/BBeOh4eDvXlrAyIiKi8jHQEGLv38bsiE1ISn8otj3XqjsmdxkIGwX/iBARkfnjb6saTBAEbPn7GL4+8TvyHg8xOdnYYnafMejl30Li6oiIiCqOgaaGSsvOxMLDW3EkPlZsa1HHF+GhYajn5CphZURERPpjoKmBLty7hdkRG3H3UarY9nybYLze6RlYKRTSFUZERFRJDDQ1iE7QYVPMUSw/uRdanQ4A4Ky0x9y+Y9G9QVOJqyMiIqo8BpoaIjUrAwsif8axW5fEttZ1G2BByHh4OtaSrjAiIiIDYKCpAc7dicecAxvxIEMttr0U1BuvdgyFlZxDTEREZPkYaKoxnaDD+rNRWHEqAlohf4jJ1dYBc/s9hy6+TSSujoiIyHAYaKqph1mPMO/gZvyVcFVsa+cVgHn9xsHDwVnCyoiIiAyPgaYaOp14HXMP/gRVZjoAQAYZXmnfF6+07weFXC5xdURERIbHQFONaHU6rDlzCKtPH4ROEAAAbnaOmNdvHDr6NJK4OiIiIuNhoKkmkjPTMffgT4hOvC62dfBuhHn9nkNteycJKyMiIjI+Bppq4GTCVcw9uBkpWY8AAHKZDJM6hOCloD4cYiIiohqBgcaC5em0WBV9AGvPHIaA/CEmD3tnzAsZh3ZeARJXR0REZDoMNBbq/qM0zD34E87eiRPbuvg2wdy+Y+Fq5yhhZURERKbHQGOBjt+6jHmHtiA1OwMAoJDJ8e9O/fFC22DIZRxiIiKimoeBxoLkabX47tR+rD8XJbbVcXDBgpDxaFPPT7rCiIiIJMZAYyHupqdizoFN+PveTbGte4Om+KDPGLjYOkhYGRERkfQYaCzAH/GxWBC5FWpNJgBAIZdjcueBGN+6B2QymcTVERERSY+BxozlavOw/K+92HT+qNhW17EWwkPD0NKzvoSVERERmRcGGjOVpH6I2Qc2Ifb+bbGtl19zzOozGs5KewkrIyIiMj8MNGYo8sYFLDy8FY9ysgEA1nIFpnQdhDEtu3GIiYiIqAQMNGYkR5uHr47/iq0Xjott3s5uWBgahqYePhJWRkREZN4YaMzE7TQVZkdswmVVotjWL6AVZvYaBUelrYSVERERmT8GGjNw4Np5LIrahsxcDQDARmGFt7sNwbPNO3OIiYiIqAIYaCSUnZeLL//cgx2xf4ltvi7uWBgahibuXhJWRkREZFkYaCRyM/UBZkVswLXku2Jb/0Zt8d/gZ+Fgo5SwMiIiIsvDQCOBvVfO4uMjO5CVlwMAUCqs8E6P4RjatAOHmIiIiCqBgcaEsnNz8PmxX7D7UrTY5udaBwtDw9DQra6ElREREVk2BhoTiXt4D7MiNuJGyj2xbVCTdpjRcwTsrG0krIyIiMjyMdCYwJ5L0fjs6C5k5+UCAGytrDGj5wgMDmwvcWVERETVAwONEWXmavDZH7vw25UzYltDN0+Ehz4Pf9c6ElZGRERUvTDQGMm15LuYFbEBN1MfiG3DmnbE9O5DYcshJiIiIoNioDEwQRCw6+IpfHHsF2i0eQAAe2sb/Dd4JJ5p3Fba4oiIiKopBhoDysjR4OMj27H/WozY1rh2PSwMDUP9Wh4SVkZERFS9yaX40AsXLqBjx45wdXXFjBkzIAhChe8dN24cpkyZYsTqKueyKhEvbf2qUJgZ2bwLVj37BsMMERGRkZk80Gg0GgwdOhTt27dHdHQ0YmNjsWbNmgrdu2/fPhw6dAgLFiwwbpF6EAQBWy8cx6Tty5GgTgYAONgoER4ShneDR0BpZS1xhURERNWfyQPN77//jrS0NCxZsgQNGzbEokWLsHr16nLvy8rKwhtvvIHFixejVq1axi+0Ah5psjErYiM+O7oLuTotAKCphzfWjnoLIY1aS1wdERFRzWHyOTQxMTHo0qUL7O3tAQCtW7dGbGxsufctWLAAWVlZsLKywqFDh9CnT59SjwnQaDTQaDTia7VabZjin6LWZGLi1m+QlP5QbBvbshve7DoINgpOTSIiIjIlk/fQqNVq+Pv7i69lMhkUCgVSUlJKvefWrVtYsmQJGjVqhFu3bmHGjBkYOXJkqXNvPvroI7i4uIhfvr6+Bv85nJX26ODdEADgZGOLj595EdN7DGOYISIikoDJf/taWVlBqSx8mrStrS0yMzPh6upa4j1r1qyBp6cnIiIioFQqMXXqVDRo0AARERHo379/setnzpyJ6dOni6/VarVRQs307kORp9NiUocQeDm7Gfz9iYiIqGJMHmjc3Nxw4cKFQm3p6emwsSl9s7mEhAT069dPDEJOTk5o3Lgx4uLiSrxeqVQWC03GYGttgw/6jjX65xAREVHZTD7k1LFjR5w4cUJ8HR8fD41GAze30ns4fH19kZWVJb7W6XRISEhAgwYNjForERERWQaTB5rg4GCkpaVh3bp1AIDFixcjJCQECoUCarUaubm5xe4ZO3Ysdu/ejW3btiEhIQEzZ86ERqNB9+7dTV0+ERERmSGTBxorKyusWLECr732Gjw9PbF161YsXrwYQP6Kp19//bXYPYGBgdi8eTPCw8PRuHFj/Prrr9i1axecnJxMXT4RERGZIZmgzza9BpSYmIjo6Gh069YNHh7G3UlXrVbDxcUFaWlpcHZ2NupnERERkWHo8/tbsjXG3t7e8Pb2lurjiYiIqBqR5CwnIiIiIkNioCEiIiKLx0BDREREFo+BhoiIiCweAw0RERFZPAYaIiIisngMNERERGTxGGiIiIjI4km2sZ4pFWyGrFarJa6EiIiIKqrg93ZFDjWoEYEmPT0dQP6p3URERGRZ0tPT4eLiUuY1kp3lZEo6nQ5JSUlwcnKCTCYz6Hur1Wr4+vri9u3bPCfKiPicTYPP2TT4nE2Dz9l0jPWsBUFAeno6vLy8IJeXPUumRvTQyOVy+Pj4GPUznJ2d+R+MCfA5mwafs2nwOZsGn7PpGONZl9czU4CTgomIiMjiMdAQERGRxWOgqSKlUom5c+dCqVRKXUq1xudsGnzOpsHnbBp8zqZjDs+6RkwKJiIiouqNPTRERERk8RhoiIiIyOIx0BAREZHFY6Apx4ULF9CxY0e4urpixowZFdp+ucC4ceMwZcoUI1ZXfej7nD/88EPIZLJiX4cPHzZNwRaqMn+eP/30U3h6esLZ2RmjRo1CcnKyCSq1bPo+Z0EQ8Mknn6Bx48Zwd3fH5MmTkZGRYaJqLVtycjL8/f0RHx9foeujoqLQrFkzuLu7Y8mSJcYtrhrR9zkDwLVr1+Dm5ma8oopgoCmDRqPB0KFD0b59e0RHRyM2NhZr1qyp0L379u3DoUOHsGDBAuMWWQ1U5jm/9957SElJEb9iYmLg4eGBoKAg0xRtgSrznI8cOYK1a9fiyJEjOHPmDLKzs/HOO++YpmALVZnnvHr1anz11VfYsGEDjh07hpMnT+K1114zTcEWTKVSYciQIRX+JfvgwQMMGzYM48ePx/Hjx7FhwwZERkYat8hqQN/nDABxcXEYPHgwUlJSjFdYUQKVaseOHYKrq6uQkZEhCIIgnDt3TujevXu592VmZgoBAQHC6tWrjV1itVDZ5/y0V199VVi0aJExyqs2KvOcP/30U2HGjBni6/Xr1wtdu3Y1ap2WrjLPuWfPnsLSpUvF17/++qvg5ORk1Dqrg379+glLly4VAAhxcXHlXv/FF18IgYGBgk6nEwRBEHbu3Ck8//zzRq7S8un7nAVBEJo1ayZ88skngiljBntoyhATE4MuXbrA3t4eANC6dWvExsaWe9+CBQuQlZUFKysrHDp0SK9hqpqoss+5QFJSEnbs2MHhvXJU5jm3bNkS27dvx/Xr13H//n2sXr0aoaGhpijXYlXmOatUKtSvX198rVAooFAojFpndbBixQpMnTq1wtfHxMSgb9++4pl+nTp1wpkzZ4xVXrWh73MGgD179mDMmDFGqqhkDDRlUKvV8Pf3F1/LZDIoFIoyu9Bu3bqFJUuWoFGjRrh16xZmzJiBkSNHMtSUoTLP+WnffvstwsLC4OjoaKwSq4XKPOcBAwagcePGaNSoETw9PZGRkYH33nvPFOVarMo857Zt22Lnzp3i6x9++AH9+/c3ZpnVQkBAgF7XF/134+zsjMTEREOXVe3o+5wre09VMdCUwcrKqtiuh7a2tsjMzCz1njVr1sDT0xMRERGYPXs2Dh8+jKioKERERBi7XItVmedcQKvVYuXKlZxvUAGVec5btmzBzZs3cenSJSQnJ6Nly5Z44YUXjF2qRavMc160aBFOnjyJnj17ok2bNti8eTPefPNNY5da4xT9d1PRv2fIMjDQlMHNzQ0PHjwo1Jaeng4bG5tS70lISEC/fv3E/2icnJzQuHFjxMXFGbVWS1aZ51wgMjIS7u7uaNasmbHKqzYq85w3bdqE119/HYGBgXBzc8PSpUuxfft2pKamGrlay1WZ5+zn54fY2FisWLEC9evXR2hoKHr27GnsUmucov9uKvr3DFkGBpoydOzYESdOnBBfx8fHQ6PRlLkMzdfXF1lZWeJrnU6HhIQENGjQwKi1WrLKPOcCW7ZswbPPPmvM8qqNyjznvLw83Lt3T3x9584dAPk9Y1Syyv55lslkcHZ2xoEDB7B48WJjl1kjFf13c+7cOXh7e0tYERkSA00ZgoODkZaWhnXr1gEAFi9ejJCQECgUCqjVauTm5ha7Z+zYsdi9eze2bduGhIQEzJw5ExqNBt27dzd1+RajMs+5wN69e9GnTx9TlWrRKvOcu3fvjhUrVuDbb7/F2rVrMW7cOHTt2hW1a9c2dfkWoyp/nsPDwzFmzBi0a9fOVOVWS6U952HDhuHo0aOIjIxEXl4ePvvsMzzzzDMSVFg9lPfn2eRMtp7KQu3YsUOws7MT6tSpI9SuXVu4cOGCIAiC0KBBA2HHjh0l3rNnzx6hbdu2gq2trdCiRQvh6NGjJqzYMlXmOV+7dk1QKBRCenq6CSu1bPo+56ysLGHKlCmCl5eXYGNjI/Tq1Uu4du2aiau2PJX583z16lXB2dlZuHXrlgkrrR5QZDlxWc952bJlgrW1teDu7i40aNBAuHv3rmmKrAb0ec6CIAhxcXEmXbbN07YrIDExEdHR0ejWrRs8PDykLqfa4nM2DT5n0+BzNl/Xrl3DxYsX0atXLzg7O0tdDhkIAw0RERFZPM6hISIiIovHQENEREQWj4GGiIiILB4DDREREVk8BhoiIiKyeAw0RGR0hw8fhkwmg0wmg7W1NVq1aoV9+/YZ9P39/PzKbSOi6ouBhohMwtnZGSkpKbh16xbeeustjB49GklJSUb7vB49euD8+fN63+fn54fDhw8bviAiMioGGiIyCZlMhlq1aqFevXp49dVX4efnh6ioKKN9npWVFTdNI6pBGGiISBJWVlbIzc3FxIkT8eGHH+LHH39EYGAgvvnmG/GaU6dOoXPnznBxccHIkSORlpYmfm/VqlXw8fGBl5cX9u7dW+z9SxtyOnjwIFq3bg0nJycMHDgQCQkJAIABAwZAJpPh5s2b6NOnD2QyGQ+JJLIgDDREZHIRERG4fPmyeGjrvn37sHz5cixZsgQjRowAAKSmpmLgwIEYPHgw/v77b2RmZuKdd94BAMTExODNN9/EsmXLsG/fPmzZsqVCnxsfH49hw4Zh+vTpuHjxImrVqoU333wTALBt2zakpKTA19cXu3fvRkpKCqZNm2b4H56IjMJK6gKIqGZIS0tDrVq1kJ2dDVtbWyxfvhwNGzYEANy4cQNXrlyBi4uLeP2ePXtgbW2NOXPmQCaTYdq0aXjxxRcBADt37kRoaCiGDx8OAJgxYwY+/vjjcmvYuHEjgoODMXHiRADAp59+inPnzgEAHBwcAAByuRyOjo6oVauWgX5yIjIFBhoiMgknJyecO3cO1tbW8PLygkwmE783YcKEQmEGyD/c8cGDB3B1dQUA6HQ6pKenIzs7G3fu3IGvr694bUBAQIVqSEhIKDQM5ePjAx8fnyr8VERkLjjkREQmIZfL4efnB29v70JhBnjSO/I0Hx8fdOjQAefOncO5c+cQExODs2fPwtraGnXq1Cm0QurWrVsVqsHX1xdxcXHi6ytXriAoKAg6na5QnTyzl8jyMNAQkVkaPHgwbt68iZMnT0KhUOCnn37CgAEDIAgChg8fjn379uG3337DP//8g08//bRC7zl+/Hj88ccfWLNmDW7fvo3w8HDUqVMHcvmTvwobNWqEvXv34s6dOzh48KCxfjwiMjAGGiIyS7Vq1cIvv/yCzz//HE2bNsWOHTvwyy+/wMrKCu3bt8eSJUvw6quvYtCgQRg4cGCF3tPPzw+7du3CkiVL0KJFC6SmpuKHH34odM1nn32GvXv3wt/fH/PmzTPGj0ZERiAT2LdKREREFo49NERERGTxGGiIiIjI4jHQEBERkcVjoCEiIiKLx0BDREREFo+BhoiIiCweAw0RERFZPAYaIiIisngMNERERGTxGGiIiIjI4jHQEBERkcX7f3ZvAOyyic8YAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "history = {'Test Loss': [], 'Test Accuracy': [], 'Predict':[]}\n",
    "def loss_function(m, b, points):\n",
    "    loss = 0\n",
    "    n = len(points)\n",
    "    for i in range(n):\n",
    "        x = points.iloc[i].前一天用水量\t\n",
    "        y = points.iloc[i].实际水量          # points.iloc[i]['实际水量'],用来访问列\n",
    "        loss += (y - (m*x +b))**2     # ------ 随着循环进行, m, b越来越接近一个固定值, loss趋于不变 \n",
    "    loss = loss / float(n)\n",
    "    history['Test Loss'].append(loss)   # 损失函数：均方误差（Mean Squared Error, MSE）\n",
    "\n",
    "def accuracy(m, b, points):\n",
    "    accuracy = 0\n",
    "    n = len(points)\n",
    "    for i in range(n):\n",
    "        predicted = m * points.iloc[i].前一天用水量 + b\n",
    "        actual = points.iloc[i].实际水量            # points.iloc[i].实际水量,通过行索引访问行的\n",
    "        if abs(actual - predicted) < 0.05:\n",
    "            accuracy += 1\n",
    "    accuracy = accuracy / n\n",
    "    history['Test Accuracy'].append(accuracy)\n",
    "    \n",
    "\n",
    "def gradient_descent(m_now, b_now, points, L):\n",
    "    m_gradient = 0\n",
    "    b_gradient = 0\n",
    "    n = len(points)\n",
    "    max_y_value = points['实际水量'].min()   \n",
    "    # 假设 points 是一个带有 '前一天用水量' 和 '实际水量' 列的 pandas DataFrame\n",
    "    for i in range(n):\n",
    "        x = points.iloc[i]['前一天用水量']  # 访问 '前一天用水量' 列\n",
    "        y = points.iloc[i]['实际水量']   # 访问 '实际水量' 列\n",
    "\n",
    "        m_gradient += -(2/n) * x * (y - (m_now*x + b_now))\n",
    "        b_gradient += -(2/n) * (y - (m_now*x + b_now))\n",
    "\n",
    "    m = m_now - m_gradient * L\n",
    "    b = b_now - b_gradient * L\n",
    "    return m, b\n",
    "\n",
    "m = 0\n",
    "b = 0\n",
    "L = 0.1\n",
    "epochs = 600 # 增加迭代次数以获得更好的收敛性\n",
    "\n",
    "for i in range(epochs):\n",
    "    if i % 50 == 0:\n",
    "        print(f\"Epoch: {i}\")\n",
    "    m, b = gradient_descent(m, b, train_data, L)\n",
    "    loss_function(m,b,train_data)\n",
    "    accuracy(m, b, test_data)\n",
    "\n",
    "for i in range(len(test_data)):\n",
    "    history['Predict'].append(m * test_data.iloc[i]['前一天用水量'] + b)\n",
    "\n",
    "print(f\"最终 m 值: {m}, 最终 b 值: {b}\")\n",
    "plt.scatter(data.前一天用水量, data.实际水量, c='k',marker='.')\n",
    "plt.plot(list(range(0,3)),[m*x+b for x in range(0,3)],linewidth = 2.0,color = '#FF4191')\n",
    "plt.show()\n",
    "plt.plot(history['Test Loss'], label='Test Loss')\n",
    "plt.title(\"Test-Loss\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()\n",
    "plt.plot(history['Test Accuracy'],color = 'b', label='Test Accuracy')\n",
    "plt.title(\"Test-Accuracy\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.ylabel(\"Accuracy\")\n",
    "plt.show()\n",
    "plt.scatter(history['Predict'], test_data.实际水量, c='#EE4E4E',marker='.')\n",
    "t = np.arange(0.6, 1.1, 0.1)\n",
    "plt.plot(t, t, linewidth = 2.0, color = '#379777')\n",
    "plt.title(\"Actual-Predict\")\n",
    "plt.xlabel(\"Predict\")\n",
    "plt.ylabel(\"Accuracy\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Simple Linear Regression  **VS**  Multiple Linear Regression\n",
    "在理解一元线性回归的基础上，我们了解多元线性回归：\n",
    "\n",
    "$$\n",
    "\\Large Y = m_1x_1 + m_2x_2 + m_3x_3 + ... + m_nx_n + c\n",
    "$$\n",
    "用向量表示为：\n",
    "$$\n",
    " y = \\theta^T x  \n",
    "$$\n",
    "\n",
    "$$   \n",
    " x = \\begin{bmatrix} x_1 \\\\ x_2 \\\\ \\vdots \\\\ x_n \\end{bmatrix}, \\quad \\theta = \\begin{bmatrix} m_1 \\\\ m_2 \\\\ \\vdots \\\\ m_n \\\\ b \\end{bmatrix} \n",
    "$$\n",
    "-----------------------\n",
    "1. 变量选择问题    \n",
    "            自变量 x 数量越多，线性回归预测的准确率不一定越高      \n",
    "            \n",
    "                                \n",
    "![](./source/2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "实际水量       1.000000\n",
      "天气         0.222637\n",
      "最高温        0.895543\n",
      "最低温        0.890234\n",
      "是否为周末     -0.023506\n",
      "前一天用水量     0.970074\n",
      "前8小时用水量    0.960844\n",
      "日期         0.926723\n",
      "Name: 实际水量, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'\\n通过图像以及数据可以看出，用水量数据与天气线性相关性最差，与前一天用水量线性相关最明显\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "预处理好的数据： train_data(DataFrame), test_data(DataFrame), x_train(numpy), y_train(numpy).\n",
    "'''\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data = pd.read_excel('2.xlsx')\n",
    "# train_data.isnull().sum()\n",
    "print(train_data.corr()['实际水量']) # 会返回一个新的DataFrame，其中包含了train_data中数值列之间的相关系数,相关系数是通过皮尔逊相关\n",
    "                          # 系数来计算的，它衡量的是两个变量之间的线性关系强度和方向。相关系数的值范围在-1到1之间，其中-1表示\n",
    "                          # 完全负相关，1表示完全正相关，0表示没有线性相关。\n",
    "plt.scatter( data.最高温, data.实际水量, c='k',marker='.')\n",
    "plt.scatter( train_data['最低温'], train_data['实际水量'], c='b',marker='.')  #['']访问DataFrame的两种写法\n",
    "plt.scatter( train_data['是否为周末'], train_data['实际水量'], c='m',marker='.')    \n",
    "plt.scatter( train_data['前一天用水量'], train_data['实际水量'], c='y',marker='.')                   \n",
    "plt.show()\n",
    "\n",
    "'''\n",
    "通过图像以及数据可以看出，用水量数据与天气线性相关性最差，与前一天用水量线性相关最明显\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "  由于观察到‘实际水量’与‘日期’的相关性为0.926723，不考虑舍弃。而x_train中‘日期’的数据类型为Timestamp对象，    \n",
    "  其他变量为float类型，需要进行类型转换才能使用modle = LinearRegression().fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(210, 1)\n",
      "0.017763022490357706 0.0005514190513391422\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>天气</th>\n",
       "      <th>最高温</th>\n",
       "      <th>最低温</th>\n",
       "      <th>是否为周末</th>\n",
       "      <th>前一天用水量</th>\n",
       "      <th>前8小时用水量</th>\n",
       "      <th>日期</th>\n",
       "      <th>实际水量</th>\n",
       "      <th>预测水量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.241379</td>\n",
       "      <td>1</td>\n",
       "      <td>0.537982</td>\n",
       "      <td>0.442314</td>\n",
       "      <td>1.549066e+09</td>\n",
       "      <td>0.478867</td>\n",
       "      <td>0.530290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>1</td>\n",
       "      <td>0.478867</td>\n",
       "      <td>0.414374</td>\n",
       "      <td>1.549152e+09</td>\n",
       "      <td>0.451904</td>\n",
       "      <td>0.480458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>0.034483</td>\n",
       "      <td>0</td>\n",
       "      <td>0.451904</td>\n",
       "      <td>0.390795</td>\n",
       "      <td>1.549238e+09</td>\n",
       "      <td>0.432096</td>\n",
       "      <td>0.458393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>0.103448</td>\n",
       "      <td>0</td>\n",
       "      <td>0.432096</td>\n",
       "      <td>0.376177</td>\n",
       "      <td>1.549325e+09</td>\n",
       "      <td>0.371817</td>\n",
       "      <td>0.442204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.394737</td>\n",
       "      <td>0.137931</td>\n",
       "      <td>0</td>\n",
       "      <td>0.371817</td>\n",
       "      <td>0.364750</td>\n",
       "      <td>1.549411e+09</td>\n",
       "      <td>0.367500</td>\n",
       "      <td>0.427100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.758621</td>\n",
       "      <td>0</td>\n",
       "      <td>0.889268</td>\n",
       "      <td>0.855854</td>\n",
       "      <td>1.567037e+09</td>\n",
       "      <td>0.923363</td>\n",
       "      <td>0.905229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.894737</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0</td>\n",
       "      <td>0.923363</td>\n",
       "      <td>0.913539</td>\n",
       "      <td>1.567123e+09</td>\n",
       "      <td>0.940460</td>\n",
       "      <td>0.936444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>1</td>\n",
       "      <td>0.940460</td>\n",
       "      <td>0.888873</td>\n",
       "      <td>1.567210e+09</td>\n",
       "      <td>0.919657</td>\n",
       "      <td>0.928430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>1</td>\n",
       "      <td>0.919657</td>\n",
       "      <td>0.829210</td>\n",
       "      <td>1.567296e+09</td>\n",
       "      <td>0.863522</td>\n",
       "      <td>0.883615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0</td>\n",
       "      <td>0.863522</td>\n",
       "      <td>0.828784</td>\n",
       "      <td>1.567382e+09</td>\n",
       "      <td>0.894872</td>\n",
       "      <td>0.859026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           天气       最高温       最低温  是否为周末    前一天用水量   前8小时用水量            日期  \\\n",
       "0    0.833333  0.263158  0.241379      1  0.537982  0.442314  1.549066e+09   \n",
       "1    0.500000  0.263158  0.068966      1  0.478867  0.414374  1.549152e+09   \n",
       "2    0.333333  0.315789  0.034483      0  0.451904  0.390795  1.549238e+09   \n",
       "3    0.333333  0.315789  0.103448      0  0.432096  0.376177  1.549325e+09   \n",
       "4    0.833333  0.394737  0.137931      0  0.371817  0.364750  1.549411e+09   \n",
       "..        ...       ...       ...    ...       ...       ...           ...   \n",
       "205  1.000000  0.894737  0.758621      0  0.889268  0.855854  1.567037e+09   \n",
       "206  0.833333  0.894737  0.689655      0  0.923363  0.913539  1.567123e+09   \n",
       "207  0.833333  0.763158  0.724138      1  0.940460  0.888873  1.567210e+09   \n",
       "208  0.500000  0.684211  0.689655      1  0.919657  0.829210  1.567296e+09   \n",
       "209  0.500000  0.763158  0.689655      0  0.863522  0.828784  1.567382e+09   \n",
       "\n",
       "         实际水量      预测水量  \n",
       "0    0.478867  0.530290  \n",
       "1    0.451904  0.480458  \n",
       "2    0.432096  0.458393  \n",
       "3    0.371817  0.442204  \n",
       "4    0.367500  0.427100  \n",
       "..        ...       ...  \n",
       "205  0.923363  0.905229  \n",
       "206  0.940460  0.936444  \n",
       "207  0.919657  0.928430  \n",
       "208  0.863522  0.883615  \n",
       "209  0.894872  0.859026  \n",
       "\n",
       "[210 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "import numpy as np\n",
    "\n",
    "train_data.iloc[:, 1:8]   #   x_train  不一定非得转成numpy数组，ndarray，DataFrame操作起来同样方便\n",
    "train_data.iloc[:, 0:1]   #   y_train     无非就是得多加一个‘ .iloc  ’\n",
    "model = LinearRegression().fit(train_data.iloc[:, 1:8],train_data.iloc[:, 0:1])  \n",
    "y_predictions =  model.predict(train_data.iloc[:, 1:8])        # 不论什么数据类型，经过model.predict后变成ndarray\n",
    "error = y_predictions - train_data.iloc[:, 0:1] .to_numpy()\n",
    "\n",
    "plt.scatter(y_predictions, train_data.实际水量, c='#EE4E4E',marker='.')\n",
    "t = np.arange(0.3, 1.1, 0.1)\n",
    "x = np.linspace(0, 210, 210)\n",
    "plt.plot(t, t, linewidth = 2.0, color = '#379777')\n",
    "plt.title(\"Actual-Predict\")\n",
    "plt.xlabel(\"Predict\")\n",
    "plt.ylabel(\"Accuracy\")\n",
    "plt.show()\n",
    "plt.plot(x, train_data.实际水量, linewidth = 2.0, color = '#667BC6', label = '实际水量')\n",
    "plt.plot(x, y_predictions, linewidth = 2.0, color = '#DA7297', label = '预测水量')\n",
    "plt.scatter(x, error, c='#3AA6B9',marker='^')\n",
    "plt.legend(loc=0)\n",
    "plt.title(\"Errors\")\n",
    "plt.show()\n",
    "train_data.iloc[:, 1:8]\n",
    "print(error .shape)\n",
    "from sklearn.metrics import mean_absolute_error, mean_squared_error\n",
    "'''   mean_absolute_error() : 计算模型预测值与真实值之间的平均绝对误差;  mean_squared_error() : 计算模型预测值与真实值之间的均方误差 '''\n",
    "print(mean_absolute_error(y_predictions, train_data.iloc[:, 0:1]), mean_squared_error(y_predictions, train_data.iloc[:, 0:1])) \n",
    "prediction_data = train_data.copy()  \n",
    "prediction_data = prediction_data.drop(['实际水量'], axis = 1)\n",
    "prediction_data['实际水量'] = train_data['实际水量']\n",
    "prediction_data['预测水量'] = y_predictions\n",
    "prediction_data\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <center> Multiple Linear Regression(从原理开始) <center>\n",
    "\n",
    "****************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Numpy 中 np.vstack() 和 np.hstack()   \n",
    "   np.vstack()，按垂直方向构建新数组 \n",
    "\n",
    "   ![](https://img-blog.csdnimg.cn/2019090714182168.png)\n",
    "\n",
    "   np.nstack()，按水平方向构建新数组    \n",
    "\n",
    "   ![](https://img-blog.csdnimg.cn/20190907142055558.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25hbmh1YWliZWlhbg==,size_16,color_FFFFFF,t_70)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0011447943413283243\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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x6aWX4qyzzsKZZ55ptoM///zzceaZZ+Kss87CO9/5Tpx22mljzhAiCIIgxke+4C6C2L3vzTd/jRyRGSIcDuPpp5/Ghz70IVxyySVIpVK250888UT89a9/xc0334xwOAyO41xJwgY//elP677u6aefjq1bt2LVqlWjvu5d73qXTcAQBEEQhxfWEeF5DqqqYeebsHKGhMgMcdxxx+Gee+4Z9TUcx+FjH/vYlF6X5/kxRQhBEAQx8xg5In4fj4XzIti1L4u+wRIGh8toTL15QuIUmiEIgiCIWYjhiETDIo5enjQff233yMwsaJogIUIQBEEQswxN05Av6jkikbAPq5cnzOe270rP1LKmBRIiBEEQBDHLKJYUqKp+OxoWsWheFKGgAADYsTsNVfXOGTwSISFCEARBELMMtodINCxCEDisWqq7IvmijP0Ha88AO9IgIUIQBEEQs4xc0SrdjYT1uhJbeGbnyOFe0rRBQmQWUS6Xbb1CAD1OWC6Xx3UeTdOgGp4eQRAEccSRy1uOSCSszyKzJ6y+efJEqHx3hujo6EAsFkMwGEQ6ncall16K7u5uvPTSS6hUKuju7sbKlSuhqioqlQq2b9+Oiy++GB/5yEdwwQUX4PHHH7f1FWltbcXq1asBAP/5n/+JZ599FnfccUfN6ycSCdxzzz1mk7JanHrqqSiVSkgkEq7nisUi+vv7sWfPnol9CARBEAQ0VUV++z74UjEEOpoAuEMzANDcEERTKoCB4TJ27csina0gEfPPyJqnEhIiM0R3dzcAfXLxySefjH/4h3/AMcccAwD44x//iO9+97t47LHHbMd88IMfxPvf/36zZbvRSXXnzp1YunQpvvnNb2J4eBiBQGDMtuuxWAyCIIy5zlAohHw+D1l2txpWFMUchkcQBEFMjOwLO9H7q8cAjsO8j7wDkZULbAPvDCECAOuPSWHb4zvRp4Xwl2cP4aJzFs7EkqcUEiIzRKlUwjXXXIPdu3fjG9/4hilCAKCnp8dzWvEll1yCU045Be3t7QiFQvjBD36A/fv345lnnsGTTz6JP/3pT3jyySdxyimnmMdomgZN01yD8URRxNDQkHn/ySefxF//+ldcffXVttcpioJ/+qd/wtq17qnGXV1d+MpXvjLhz4AgCIIA8tv36Tc0DT03348l//Z+W1fVaDU0AwDrMgdwTGUP+rkg7nw2gL/Z2AG/f+wvlbMZEiIzyKuvvopNmzbh9ttvBwA888wz+Md//EcMDAxAURQ8/fTTAIBPfepTeM973oP77rsP73//+83ju7u7cdJJJ+G//uu/AACCILhcjvvvvx8XXHCB7fFnn30WAPCnP/0JF110EV599VVceuml+OQnP+kaMX3FFVdg//792L9/v+d7+MhHPjIFnwRBEMTcRSnY8wAP/eJR5Ocdbd6PMI6IvEMXLc1aCXy+iKdf7sdbT2rF63vSePqlfqiqhsvftQTRiA9HCm86IbL/P34HJVs47NcVYmEs/Oy763qtoijgOA6/+93v8JWvfAWVSgV+vx+yLKOpqQlbt27Fq6++iqVLl+Kaa65BNptFf38/vv71r+OZZ57BD3/4QwBAMBhEMpkc9VrnnnsuhoeHEY/HsWfPHhx//PGmu3H77bdjzZo1+Na3voWbb74ZF1xwgXncxz72MWzatAnxeHzU8Issy/j5z3+Oc889F9/97nfrev8EQRCEhZzO2e4Xd3UjqKUACDiz0g35/3Yjf9kZ8LemIKetst1GrYTf/LETdz20H6WyVeiwqCOKc98y73Atf9K86YSIki3YflCzkZdeesnM7zhw4AD++Mc/Ytu2bfjVr35lvua8887DQw89BEB3OlauXImnnnoKN9xwgxlm0TRtzBwNNl/k7rvvxnnnnQefT1fKl156KT772c/iySefxEknnWQ77qabbgKgD9TL52t/njzP4xOf+MR43j5BEARRRdM0yCPuv7GR4WHE1DhOUgagjgCDDz6P1FnH217TqJbRKWuQZXu15Ui2Mo0rnnredOW7QiwMMRE57P+EWLjuNZ500knYuXMn7r33Xixfvhx33XUXlixZgkWLFpmvKZVKWLZsme249vZ2fO5znwPHcVBVFQMDA2hsbASAMct1K5UKfvjDH9pCKR/+8IexaNEi7Nu3r+Zx11xzDSRJwvz58zF//nx88YtfRGtrK+bPn49oNIovfvGLdb9vgiAIAnhh6yC+9aNX8NQLfVALZWiSng8SmNdoviZWyKJds9z98oE+K5ekysKgjFTcj+aGABoSVvVMseguLpjNvOkckXrDI7OJtrY2/OEPf0A2q493TqfTCAQCiEQiAOwi47LLLsNHP/pRFItF7Nq1C/Pm6fZbpVIZtX/It7/9bbS3t+Nv/uZvzMcCgQB+8pOf4KKLLsLixYuxbt0613E8z+P2228311Iul/H9738fHMdBkiRXEixBEARRG1XV8Kv79iKTk3DHfXuxJrXYfC4wvxlKvgQ5nUeynEe7wFQ/anp1DcsxjRze/in97/ZwpowvfedFAEChZHdIZju0i8wC4vE41qxZYzYu27x5M5YsWWI+XyqVAABbtmzBtm3bcNFFF2HHjh148MEHsW7dOpx33nm4+eabIcsyKhW3JXfvvffiuuuuw8033+x6buPGjbjhhhtwxhln4LbbbnMJmQ0bNuDss8/GmWeeiTPPPBOiKGLjxo0488wzcdZZZ2Hjxo1T+VEQBEG8qenuLSCT00tzJUnFji0HzefEZBSB+c0AAL+mYKUyYj/Y8fe50jts9pMKBy1foVAiR4SYIGvXrsUNN9yA73znO3j729+Ou+66C5/+9Kfh9+uW27XXXotPfepTSCQSKJVK+O1vf4tvfetbOP300/Hss8/i0ksvxTvf+U784Q9/MM/5m9/8Bn/3d3+Hm266Cccdd5zndT/0oQ8hEAjg4x//OO68807cfffdEEURmzZtws6dO9HZ2Wm+VpZlPPHEE2ZlTaVSwXPPPYeTTz55+j4YgiCINwnbd43Y7ne+3ouG6m0xGQV4DvltnQCAuCZhNNRSBUqmADERgd/Hg+c5qKqG4hHmiJAQmSHS6TT2798PUbR+BIlEAnfddRdeeukl/PjHP8anP/1pfP/738evf/1rPPjgg7j33nvxox/9CADw+c9/Hu9617vwqU99Ci+88AI++MEP4v7770cymTQdFAC46KKLzAZogF6xoygKcrmcLazyvve9Dxs2bIAoiuaajj/+eNx3331oamoyhUcymcSjjz6KYDAITdNQKBTGbJ5GEARB6Ly2y96aXRq2KmYe3jKCc09tG/McfMAHtayLlErvMMREBBzHIRwUkCvIKDhyRFRVw8G+AtqaQxCE2RcIISEyQ3zve9/Dbbfdhi984QsAgBdeeAEf/vCH0draiqeeegqpVAq33347fvzjH+PUU0/Fbbfdhi9/+ctobGzE7bffjkceeQQvvPACAOD73/8+/uEf/gHpdBo33ngjrr/+enz7298GoOeBGCIEADZt2oSzzjoLRx99NFasWGFbE5sce9999+HrX/86otGoa+3nn3++rddIoVDAxz72MXz4wx+eug+IIAhiGpBlFb/8wx4cGijhHy9bgYbk4fsiVako2LkvY3ssxrgemzuLiC2UsdRxnK85AanfEjDR45ch8+wO/Zy9wwgfNR8AEA6JyBVklyPy2wc68eenD+Ho5Ql8+gNHY7bBaezAkllIJpNBIpFAOp1GPB63PVcqlbB3714sWbIEwWBwhlY4NaiqimeeeQannXaa67kDBw5gwYIF5n1N09DT04OOjg7Xaw8dOoRyuWyrwHFe54033sCqVaumbvGj8Gb6GREEceTz4OPduPthvUHjGae04ooLnNv+9LH1jWH88HZdQJx4TANeeX0Y787vxAJVL9/9fvBYcH4RH8ltRVi1BErre89C7x3VkR8Cj46PvhPd/3MvACC+YTVaLz0DAPCtH72C/T158Dzwo29sqFZYaviXa583E1hv/Mp6REKHx4MYbf9mmX0ezRyF53lPEQLAJkIAgOM4TxEC6BU4tUSIcZ3DJUIIgiBmE0MjZdz/ly7zfmdXbpRXTz3bmbDMScc24ZTjms08kDIvQuZ4SJKKg2D6Q3FA5JjFCC3XKyQjqxaag/EA3RExMBJWVRUoV/TE1oN9BVsVzYGe2ddni0IzBEEQxJzgtw90oiJZlSfdhwqQZRXlioLX92awelkCoeD0bYuvVRNVOQ5YtTSOo5clcGCTBGhAtCWOmOxDNi+hlw9hmaqHcHzNSQihANo/cD5KnYcQWjoPfMAHMRGBnM6jcmjYHM0RDlmjPIolGcGAgJ37srY17D+Yx6pl7mnqM8mbwhGZ5dGlOQ39bAiCmGk0TcP9fz4AdcsbOEHuB6p/l2RFQ09fAT/+5Ru46Y438L+/2el5vKpqeODxbtxx315UKhOrSOk+lEdPXxEAsLgjikjYB59UBqfqa/E3xPCev9Hd7EO85YgEF7YAAIRQAJHVi8AH9M7Y/taUvrZiGUpWP2/IVsKrr3OXIydlf8/hdYHq4Yh2RIxBbpVKhcbRz1IKBb0zoNFWniAI4nCiKCpuu2s3+l7cg3dL3QCAcHMcTw3rSaovbhvCG536Zv3a7jQkWYVPtH9Hf2TTQfy+mlfSkPDj/Ld6h8ZH46+b+8zbpxyvh1bkEUsUiMkoNhzfjGhYBGQZ/vvTkIaySJyy2vN8vuYk8IYeZpIGMxDjYYSDjCNSlKFpGnZ1OhwRCs1MLaIoIhwOo7+/Hz6fj7p8ziKM0t6+vj4kk0nXVGCCIIjpoLj3EEaeeAXxk1chsnohnn6pH89uGcBpqtUu/dQ2Hk9VUyv+/LTVUExRNHT3FrC4w6oW7B0o4g+PWNPH9x4Yv6NQqSh45uV+AIDPx+OU4/SmZWzprpjUr7nmKN3p0FZdBk1RwPu8t2lfylqjIWicjsjgSBnDGXuTy77BEkplBcHA7PmbfEQLEY7j0N7ejr179446L4WYOZLJJNraxq6LJwiCmCyaouLQzx6GnM4jt60TC/7pYuypCoeUVjZfFyrlwXFJaJqV1GmwvztvChFV1XDbXbshyVaIubt3/NPdX9g6aJbUnrSmEeFq1YrdEYnYjuF4Dhxfe4s2hAt7HjZHpFCSsYvJD+F5PYlV04Cug3ksX1y7iuVwc0QLEQDw+/1YsWKFZ2tzYmbx+XzkhBAEcdjIv7bfmr6uqDj4s4eRbz8WAJBSLSEiD6TR1tSOg/1F1zn2decAtAIANr86gN377aGN/qHxOwpsWGbjya3WOpipu76ku2fTaLDCRTIckYC1pRdLMroPWaLphKMb8cLWQQB6wioJkSmG53nqUUEQBDHHST+z3XZfHspiZWkHXtbmo4FxRKTBDBafFPIWIkwOxaYX+83b7c366zUN6OkrYOmCWF1rGhgumWKmozWMJfPdTgZgdzjqwcsRCbGOSFHBrup1eR444+RWS4jMsjwRSqogCIIgjnik4SwKO/RcDiEeBh/Wk1EXFIbQrhbgBxOCUVQsSdi3PyPFsKevAElWkc5WsGOP3vejKRWwORldh+oPzxzss8TO6ckyDv3iUZQP6oKgfGgIAMCJwviFSDyi1wHDclbYwXe5goRDVaHV0RrB0gUx8z0eOEhChCAIgiCmlMyzO4BqKkfytGOQPH2N+dwaZcj1+nl+q3NpwM/jhKMbAVgJq8+/MmBU+WL92ibMbwubr+8+VP9G3jugiwFe0zB/2yvIvbQL/b/fBLUimW3b/W0N4MY5A4YTeIhxfU1mjghTNdPTWzTX39wQgM/HY16L/vqevgIq0uwZjEdChCAIgjii0VQV6Wdf0+/wHOInr0JwseVgrFRGXMcklZK5ca9dlcKyhVaoZX93Hs9uGTDvn3JcEzrarJyMrkMFPPJUD77+ny/jxS29yG7ZDTnjLU76BvUhpDGtAl7Sh9GVOg+h3D1g9jMJzGucwLu2wjNKrghVVmxVM12MWDLm6RhCRFWB4fTsyat8U+SIEARBEHOXws5uKBk9XBJZvUifRsuUvQahuo5RBzP4539Yhx2703jr+lbTuQCA517pN/MoFs6LoL26gacSfgynK9jXncPu/VloGtB/518RKwzA35bCwn+5DBzP2a5jCRHLgdFkBZkXrOZpkxIi+3oB6K5IOGaFd3IFawJvQ0IXItGI9ZnkHRN6ZxJyRAiCIIgjmiyzqcdPOgoAIIQDUBK1E0orfSNYuiCGd5w5H7GIDwvaI0bKBXZ2ZiFqeq3rKcdZc12M8Iwka2bYY2lBd04qh4ZR2nfIdR1D4DSJ9o0/++IUCZEq8kgOAT8PjnO/rrHqiLDD7vIFEiIEQRAEMWnUsoTcq3sAAHzIj/DR1tDPYipley3nEyFU8yqk/hHbcwG/gLZmvUP3QiWLT5a24v2VnThpddJ8TUervdeHk9yWPbb7kqSaDcXaQvZxF1rZckj8ExYi1nrkkRw4jkMo6C4rbkj6AQCRsNXhmoQIQRAEQUwBua17oVX0TTV63DLworURj4TtvTJ8zQn4W3RxouRLUPIl2/Onr9Pnuqzl0vBBQ4tahNjdaz7PJqwCMHM8DLJbdkNTrcf6h0rmSxoF741fTEUhhAJjvU1PfF5NzTyG9hmhGdYRyVFohiAIgiAmjy0ss+4o23O9ot3B8Dcn4W+xJs9W+kYAAOlnd6Dz+l/hlEAO3/3SSThhkTW7LL/Dau/OChGfj7eXBANQMgWUOq3wTO+glXfC5oiwBOY1eT5eD2xoRqqW8DqnB/t9PCJh/THjvwBQKHivZyYgIUIQBEEckSi5IgrVwW9iQwzBxW146oU+fOm7L+CRp3rQI/tQYrY5f3NCHxZXxRAigw88B6l/BIMPPod41GcmvgJAYccBaJqG4t5DiB46hPXHNiAaFvGPl65ACO4S2Nwru83bRqIqAIQqJddrgYnnhwA12rw7QjMNyQC4auIIK0SOWEdk69atWL9+PVKpFK666qoxR7xrmobvfOc7WLFiBZqamvDJT34S+fzsaqRCEARBHJlUeofN8Ehk9SJoAO7+0z4Mpyv4/cP7MTBcwUHeckV8LUkzNAPoeSJqRYKS1YWHPJKHpqi2Ulx5JIfMM6+h67/vwaHb/oTLlnO44cvrcfzRDehIusMg2S17zPBM30BVfGgahLx3E7TJCBEhGgKq/Ues7qr2NRn5IYA9NFM4EnNEyuUyLrjgAqxbtw6bN2/G9u3bceutt456zC233IIf/OAH+MUvfoGnnnoKzz33HK688srJrpkgCIIgIA1Zc2B8TXF09xaQzesbrCRrGBwpY69QrZzhgODCFvia4rbj2Xkv0DRIQxmoBasdPAD03fmEKXjy25lQTdKdGKpkCih36bNlDEckBAWQdffE32pPoA10TDw0w/GcmSdS0xFJWPknUdYRORKFyAMPPIB0Oo0bb7wRy5Ytw7XXXotbbrll1GNuv/12XHXVVTj55JOxcuVKfOMb38A999wz6UUTBEEQhDSUMW/7GuJ4bXfa9ZqXhUa82roU7R/6G/ibk3o4o1riKg1nIQ3bh9qV9ve5zsHClse2xaxNP+uz5p3ldhwAYOWItAWtXJLg4laICd2l4YN+iKn6ZtbUwqicUYsVqGXJlSPCCpFgQDDbvB+RfUS2bNmCDRs2IBzWk3XWrl2L7du3j3rMwMAAFi5caN4XBGHMaazlchmZTMb2jyAIgiCc2ByRhhhe2z3ieo3K8RhevATRalkvLwr6nBboQ/FsjgjGFiJK0XJLmkKWKnlVs5Jgh7fuR6msIJ3VE0I7mGIbXyqGpgtOhb+tAU0XnupqgDZenHkizvJdo4cIAHAcZ4Znjsjy3UwmgyVLlpj3OY6DIAgYHh6ueczxxx+P3//+9+b9n/70pzjvvPNGvc51112HRCJh/luwYEG9SyQIgiDmEDIjRJCIYGdn1vN1ybjfdt9wIZRcEVKffQ8rM0LEa/4LW/Kb8Fl5kr18CMOcfh2tpx99h6y1tPitpFYxFUXshOVYdNVlSJyyuuZ7qxdb5cxwzlW+y+aIAEDYECJFGbKsoliaeUFStxARRRGBgL3WORgMolCoPYXw2muvxXPPPYe3vvWtOO644/DrX/8a//RP/zTqda6++mqk02nz34EDB+pdIkEQBDGHMBwR2efD5h0ZSJK7lTsAJBxCxNdghUOKe+3dUMvd1oyZ5Ma1ehO0qBV2UXJWSa4gWyWwJQjo5PXzcpqGwVf3I6ApCGkyUry12U82FOPE5oik855VMyzRalOzUlnB7v1ZfObfn8dnv/UcHvpr95SuazzUPWumoaEBW7dutT2WzWbh9/trHAEsXrwY27dvx44dO/CFL3wBra2teOtb3zrqdQKBgEvwEARBEASLJiuQ03pYZUAW8fO7rbLZY1em8OrrltORjPlsx4qMECl19dvPq1hiJrxyAVLnnAhoGrp++HtUeodtjojCJLV2LE6is1PBCcqg/sCLr+GjpTR4aBAPWvsk24RsKjAm8AKAks0j1NFi3uc4IBX3dkQAmPN0CkUFwiRDRJOhbkdk/fr1eOaZZ8z7nZ2dKJfLaGhoGPU4juMQj8fxyCOP4Prrr5/4SgmCIAiiijSSMytZ0px9s73oHHtI3xma8aUYMaB4uyiAvskLQT+EUABCRHdFtIoMtTpFl62uef/lR2MwkjQ7i0TTwwhAhQ8aOCOvhIOZqDpVsEJEThdsjkgi5ofgCC+xJbz7enLm7aZUEDNF3UJk48aNSKfTuP322wEA119/Pc455xwIgoBMJgNJqt2l7d///d9x6aWX4sQTT5z8igmCIIg5D5sfkuYtoTGvNYQF7RG0t1jdUZMx7xyRsRCYTZ6PsOEZ3RVRCpY7IkSCaGmLoYevLTTEeAScOHrBxngR4sy8mUzeVjXTmHRHF9imZoYjAgCNqZmLRIwrR+Tmm2/GlVdeidbWVtx5552mw7F27Vrcf//9nsft2rULv/zlL/Gtb31ralZMEARBzHnYipk050dTKoD5bWFc+vbFAIC3VOfGdLSGXXkSbI5ILTi/CD5oCRghagkbJa/niRiOCOcXwYsC5rWGsIe3+pTs5x1hmGkIf4ixkFmOLGcKSMT8ZolxW5Pb5WAdkd4BS0g1zaAQqTtHBAAuvvhi7Ny5E5s3b8Zpp52G5uZmAHqYphbLly9HOu2u7SYIgiCIicL2EMlwfnzw3cuxfLElAt52WjvWHJVCYzIA3iEA6nFExHjYbI0OwAzNAFbljOGIGM/Naw3j12ITwpBRhIjnxWZc2diPSPdBAO5mZlMBJwgQoiEo2SKUTAHxqA//752L8cbeDN5+Rofr9WxTM4NIWHT1HzmcjPvKHR0d6OhwvzmCIAiCmE40RUVm8+sQIiF7aIbzuypjOI5DW3PIeQoAei8RIR62zZQBx9mm6Ypxe4jFJkRyRWiaZiarGtNzO1rCUDgej/vmma+NvvN0CHc+BHk4i/jJq8b5jutDjIWhZIuQMwVoqoazNrTjrA3tAABVksH7rK0+7CFEZtINASYgRAiCIAhiJkhvfgP9v3kcAGxhkwznR8JRGTMWvoaYTYj42xtQ6Rk07wujCZF8CVpFNhNd+bD+XHtr2HYMz3NYuDQF8fOXQS2VISamtmLGXFsiAvQMAqoKJV/SwzUA+u76K9JPb0fTOzcgdeZxAIBoyEuIzFyiKkDTdwmCIIgjhK6X9pm31VIFAJCDiEDYD79vfEmgPkd4JrS41XZfTNhFhRBhc0RK9kTVsO4oREKirVR4flsYfp8APuCbNhECOEp4qwP7NFVD+unXAFXD8J9fMgfxRTwckZlMVAVIiBAEQRBHCHKfu5N3mvcjER+fGwLYe4kAQHBxm/15pyMStTsibOkuH7Y28nmMK7J4/vSJDxbRVjmjuzxqqQKoumOj5Esod+v9UsKejggJEYIgCIIYFU3TEMjlXI+nOb+rPLcenJUzIZcQcToi9hwRtpmZELaeY4XIksMkRNgyY7nqiLCODQAUXte7lBudVVkoNEMQBEEQHiilCrIv7YKczkPJFCAq7rkoen7I+IUIWzkjREMQU1GYo2lRzbtgYIWIWiM0AwAbjm9GwM8jlfDjuNWjN/ycKrwcEbYDLADkX+9C/vUD6LnuF3hXZZ/tuZl2RChZlSAIgpiV9P3mL8ht2QN/awpNF51mPt7JR9GhFiBCRScfw7HxyTkiYioKjuchJsKQh3XXxemI8H4fOL8IrSKPGppZ0B7Bd790EkSBhyAcnrbpbD6LUm177xQipc5e9Nys9/tahQKeUNuR4fWeI84+K4cbEiIEQRDErEPOFJB7ZS8AoNI7jNzL1iyZHUISD/kWQISGYT6At0wkNJOKQUxEIKfzZqKqLxXThQjHuXJEAN0VkSs5KPnaoRkACPintnvqWNjavBs5IsxwPv0Beyv7IGRkoLtJPnFmgyMkRAiCIIhZR/alnba+HtkXd5q3B/kgskxb9+QEklU5UUDHxy9AqbMX0WOXAABSZx8POZ1H7MQV4APucwqREOThHJR82eyuCtgdkZlAiIb17qoakyPicESc+DVdmMx0WAYgIUIQBEGMgqZptg6jh4vsCztt9zVZMW8PcnYHwjnUrl78zUn4m5Pm/cjqRYisXlTz9WbljKZBGrA6uwozLEQ4gYcQDUPJFszeKKxj40WgOp5vNggRSlYlCIIgXGiahoO3/wl7v/kz5LZ2HtZrlw8Nodw94PlcFj5UOHvoYyJVMxOBTViVBqzRJc7QzExg5InI2QI0VbU5Nv52d9Ks4Yg0znDFDEBChCAIAgAw9MgLOHjbnyANu0tE5yLSQBq5LXugZAo4+NMHUTrQf9iuzbohbAdVABjk7d/gOQ6IR8cfmpkIbFOzSt+IeXumQzMAIMSqeSKqpjdcY0Iz7X9/Ltr+4Tw0XXiq+Rg5IgRBELOI8qEhDD7wPHKv7EH6qa0zvZxZgeqw9g/+9EEz/2C6yb68S7/Bc2h8+3rbc86wTCzigyAcnq2MdUSM/BXOJ9pmucwUIlNuLKcLNiEiNsYRW7sUvgZrKKBfU8BxwNIFYw8AnG5IiBAEMedhv93KI+SIAIBalmz35XQeA/c/O+3XlXNFc6BdaHEboicstz0/wNuFyER6iEwUtruq+dgscEMAd5t3Q0hyAR94UQ9l8SHrs1q/KoFPf+DomoMBDyckRAiCmPPIg1bioVKdYTLXcQoRAKgcHJr267LXCHQ0QoyGEOhoMh8b5ILgeSt5diIVMxOFDc2Yjzn6jcwU9qZmeTNHhHVx+IAlRNriAlYvSxy+BY4CCRGCIOY80rA1Ul4tjl5tMFfwEiJqxf3YVFM+aE3A9bc1AgDi61cCALIQ0ceHsGietekeVkck4nZEUhvXHrbrjwbbCdYoMQYcQoRxRNTS9P8s64WECEEQcx5piBUi5IgAgFp2fw5axd1ifaqxOSLz9GqPxOlr8OKa9bgtuBIyx2P5Yiuv4XBVzABuIdL49vWInbjisF1/NNhOsaUD/WYOSy1HRJ1Fzh8JEYIg5jwyI0QUckQA1HBEPB6bakxHhAP8rboQ4XgOh7gQSpyeFHraiS0I+HnwPLB2VWra12Tga07A36pfL7nxWKTOOfGwXXssfE0JvakZgNK+XvNxmxAJWmGs2SREZj7VlyAIYgbRNM0Rmpk9f6BnEs0zNDO9joimqqgcGgYA+Brjtu6m2by+HkHg0N4cwre/sA4VST2soRmO57Hgs++GnM7D3zQ78isMeFGAmIpBHsraRAbb44T3ieAEHpqizqpcKHJECIKY0yi5ki3koEkyVKaL51zF5n4Y5bGqautwOtVIgxlokv6z8Lc32p7L5vT1xMIiOI5DKCgeVhFiwPvEWSdCDLzW5QwnGX1ZZpMjQkKEIIg5jTyccT021a6IWpHQd9dfMfjAc9CY+SmzGVaIiDGrMmQ6E1bLbH4I0w1U0zRkC7pAiUYOX5XMkYaPaVdvwNcUIpSsShAEMSuQBrOux9TS1OaJZDa/gfRT2zD0yIso7jk4peeeLlghIsRCzOPTF56p9DAVM4wjUiwpUBRdwMVIiNTE3zw+R2S2iGISIgRBzGnY/BCDqS7hldiGaUPu603ZdQYz6PrRPei768lJbzJs1QzriGjT6Ygc8nZEjPwQAIgdpnbuRyK+cQiR6Q6zjQcSIgRBzGkkD2GgTHFoRk5brdGnsyqn56cPobj7INJPbUX5QN+kzsUmptockWkUIoYjwvlE+BqtduQ2IUKOSE38HqGZmkIEsycxm4QIQRBzGi+HwjlnZdLXYITIdDZMqzDNwORscZRXWmiahsLObkiO1vZaNZmRE3hb5cV0Vc6oZQnSkJ6v429LgeOt7YmESH2IqaiVWFzFLUSYEl6PXjEzAQkRgiDmNMbmxzLVFQWHS4iwcNX5ImMx/OhL6P7xvdh/w502t8PIEeECPnB+q9ODV1nvVFA5NARUo0kBZ8VM3hI/sQh1nagFx/OuyhlWRALkiBAEQcwqNFWDPOwecjdW+ESVZGhKffF1TdUgZwrMuafnj7/icHE0aez1qWUJgw88p98ulFDpS1vPVUUJH/DZ+nmwYkVTNeS370O5e2BSawfsFTN+Jj8EsEp3AXJExsLHCBE+6HcJUpsQmSUlvCQtCYKYsyjZgpmwx/lFs5/IaN8UpaEM9v/HXYCmofmS0xFfd9To18gVAVU170912Meg0jdsu6/JY4dQMs+/bruvFqzR8YYjwgf84P2sELHOm315F3p/8SjAAfM+/A5EVi+c0NoB+4yZwDynI0LJqvXCJqzyHpOBbULkMHTKrQdyRAiCmLOwiaqBedaE19HCJ/lt+6AWSlCLZfT+8s/o/dVjoyZwsmEZYPqSVStMZQ4wtiOiqSpG/vqK7TElXzKfM0QZP0poprBjf/VBoOd//4jv/cdzyOTG3tzkTB6qZBdKthkzbXZHpPuQ5SgdztkyRyJsCa/XkD57aGZ2jDMgIUIQxJxF6h8xb7Oj5tnwSXFfLw788G4M/2WL/lzecg0A3VXo+tEfIKfdIR7ALUSmKy4v9dodEedG7yS/bR+kAXt+jFJ1RFjXgw/4ajoiznDQ+u4d+Mum7prXlNM5HPzZw9j7jZ9h33d+bX4j1zTNdESEeBhC1KrSyeQk7Nynr7O1KYhUgoTIaLChGU8hwobZZokjQqEZgiDmLCWmxDW8fB7ST20FYP+mOPCHp1Hq7EVpfz8Spx5tbtYs5QP92P/9uzD/kxe5kgXljFOIHCZHZIweEelN21yPGcJCY6opXMmqjPujOETWPK2A4d1dABabj+Vf24+hR1+Eki1CHsmZ65KHsijuPYjIqoVQMgUzZOV0Q7a8NmQMksUJRzeC47hR39dcJ9DeCE4UoMmKOaCPhQ9Z4ZrZMm+GHBGCIOYspX1VIcIBoRUd5uOHutLo6StAKZStSaaqCjlbgJK3hET7B87XSyYBKJkChh99yXWNwxeasTsixaz9OkquiMLuHmiqClWSPTu8qlW3h23/7XZErOecIgsAGkRLAGmqht5f/wWlvYcgDaRd4qhc7RvC5of4HfkhL223QjYnHGMXKYQbIRJE+wffjobz1qHh7BPczwdm3wReEiIEQcxJ1IpkboD+tgYIoQC46h9pqVDGPQ/vR2FnF8B0KFXzJVtC5wO7JDzcvsa879UczSlEtEr9FTd1vxdZcbWqHx62+ohoioL93/8dun/0Bww98iJKnb2mKAguaTNfZ4VmHEIk4A7NqLICJed2h9iBgZVDQ1Cyen4HJwoQG2KIHrfUfN4QIpUaM2YKRRk79uiVPKmEH4vmRUb/IAgAQGTVAjSev94W4jLgQ1Q1QxAEMSsodw0Aqi4yggtbAACyIEKAhKCmoHewhMKOQ7Zj5HzJCs1wHB7ZrJetbgQgwHtGjTziVR5cgeixSUwUqT9tE0wAUMhZa5GGsmaZ8tBDm5E663jzudhxy1Daq79PI/+FzR3g/d7JqmxYRgIPH/TKIDaHpLCzy7zd+M5TkNq4FpqsYNfWTkBRzU6qtooZpofIq68PmzNmTji6gcIyUwAfICFCEAQxKzBDLgCCi1oBAAWVRwxAAArS6TLyw/ttx6i5oplHofr9QHVjLENAGIpnIqrC9BAxz1MsA1MgRIYfexlDf34JvM/9p7zElLw6k0pHmPyQ6Nql6L/nKUCzXseGZrbsyWL1MZbLYQgN1ukZ4fxo1qoVN7JVqlzYaSWuhlfMB6A7I/7WFCo9g6j0j0CVZKuHCM/Bx+Q1PPeK1Z/kxGPsIRtiYsxGR4RCMwRBzElK+61E1eDCVpTKCtLV/VeEhngx5xIRSr5k5lHIPitcUeb0plFS3h2qcIZmgKlJWFUKZQw++DzUQtnzGuWCtck4K30MV8PfloKYiIAP6gmMZo4IE5rZ2VPEDbfvsNZefc4pRMxzV6t1NEUx81CEWAj+thRyBQmapll9QlRNFyTVih9/cxJ8tQHXzs4Mtr4xAgBIxnxYtjBW1+dCjA4/C3NEyBEhCGJOYjgifMAHf2sSL2wbQlGzulCukoddx8iZvBm2KPMiUDUKytCPU0v6RmuEENSy5PnHXilMfgPIvrRz1MoYiXE11Jz33JnQcj1BV4gEoBbLyA8XcNMdr+OyhdaxEnjkmOVqHo5Img+gGpmBWs1/KR3oNwVPaHkHHn+uF3fcuxdL5kfxgaVJ6328vAtQ9IONjqqqquE3f+w0X3PB2xaA5yksMxVwggDOJ0KTZJvzNZOQI0IQxJxCUzVIIzlzIw0saAHH83h5+5DpbADAKmXEdWyl32qBXoL1WuM4Hpq5UQPebggwNY4I2xWVD7v7RagVGZVqUzOnI2IQrlYKGcf7VRkvbR3E/n3W+6xwAsBxkKALgXxGFzU1HZFqaKZoC8t0YNOLugO1tyuH379sJdYOP2WFiYLzmwEAz20ZwP4e/fzz28I47cQWz/UTE8NoajZbHBESIgRBzBkKO7ux9xu3ofPff24+FlzUAklW8eobI6azAQBRVDuLMjF1ienVkdP0P588D3BMAqDEVJKwm7UQtcTCZEt4ywcHUT7QDwAIzG/Coqsuw+Cao/Ebv1WRIkLFwJB+HU8hwnEILZsHABipWG5DEAqGB6x1V8Dj7FPbIFU/m9xICQcO5m0N3FghwlUdEVt+yPIO7Ou2zrkjzTOv14ULJwqInbQSqqrhD48eMJ9/z9sXkRsyxRgTeEmIEARB1EHpQB+Gn3jFlXA5EUae2qqXnDIFJsHFbdj2xghKZcXmiBhEjlls3mbLczOy/uczEfVDjFhNogb7rNewQsTPNOqaTHdVpVjGyJNbzfvx9asgxsPY0zQfPbxV3ipAQ9+gLkC8hIg2rwU3/Gwnvn3Tq+gctNYT0mRkmdJfX9iPy96xGHxAj+SLmoqf/363wxFhZpooKjRFQalTr8QRG2KQwmHbtYuciCzsM2P8a5dDjIWwfdcIBkf0n/XRyxNYvTxZ1+dC1I/piJQr0FRtjFdPP5QjQhDErEWVZHTffD/UQhnSQBotf/vWSZ2PLaUVG2IILWlDZNUCPPvrnQCAkocQCR81X58vUyzbSmTTEgf4gGTCD38lCFQLPIZ6c5i3uno9xjXwtzaguKtHf18TcEQ0VcPBnz6I/PZ95mOcwCN24nIAwMBQGTIs50CEit5BXVCwQqTjExeivL8PP9smY/d+XTQtVK33HdQUlJmmbU0tUXAch1gyBKm3BD9U7OvJQ/brQqQAARWOdTj06iHNyPtoTWFg2Lr+UUviiEV8qOyMAyN62a4G4IF0DB9RNfx1s5VEfOYpVo8TYuow581oeqdcLjizbfNJiBAEMWuRh7Jm6+/ibncn0PFiVMEIsRCWfOV9+nlLMl55XU9M5QJ+wJG/F14+D0Ik6BIPJU7/85mK+xGqWKW4I0xYg3UN2EZdEwnNlHsGbSIEAKInroBQze8YGC4BHAcZHERoEDUNB0xHxHI4QotaEVrajt1PPu96LwAQggw/rBLc5ja9WkUI+CABer8QVTO7quY4H8CMmudU1dbUjPeJODRkvd/VyxJ4x5nzMfDHYQw/qguRnXwCL/ZI+NX9e/HKDv1nkYj5sOYod4tyYvLYJ/BWbPdngnGFZrZu3Yr169cjlUrhqquugqaNbel897vfRWtrK+LxON797ndjcHBwzGMIgiAAQGbKZyt9I2POTxkNTdUgZ/UNWYxZoYIXtw1BlvW/ZQsW2ze+nD8EMRH1HB5muCfJuB+xBut8mSEmv6J3xLwd6LD6YEzEEWHFRHBRK1resxEtl7xFP5+qYXC42gOk6k6IUF2hGT7oBycKyOQklMr6Z7l6WQLnn7fEPHdIk+HXLCEyr0MXIhzT5j2uVcxmcDnOh1jcCs3wmgqlZCXscj7B5og0N+ifZfSYxQAHaAKPZ3x6Murjz/ZCrZ731BNaIAiUGzIdsMJDmaYhjOOhbiFSLpdxwQUXYN26ddi8eTO2b9+OW2+9ddRjnnjiCdx222144okn8OKLL6JUKuFf/uVfJrtmgiDmCLZZJqqKykC69ovHQCmUAFXfYIW4JRye3dJv3l652t4066BPnyPj1Sq7WDWUU4kAEo1WbkZxRBdPuYKEXHWWTcXnB5eyhuFNJEeETSyMrFmMxKlHmz0h0rkK5GoHUk0whIiGfocQMQRV74AlDNpbQogx6w9pCvywBN/8Bfq6eaa7aoNmCaks50Mibgk1QdNQYdbK+URzHYAlRIKLWrHoi5djyZcuxxnvOtr1ft+yjiplpgshOLsm8NYtRB544AGk02nceOONWLZsGa699lrccsstox7z3HPP4R3veAdWrlyJ5cuX473vfS/eeOONSS+aIIi5gbOhWOXQUI1Xju9cYlzfeIczZbyxVx8x39IYxLwFSdsxu1VdsHg5IsWqI5KK+xGMW0KllC1j284RfOs7z0CQ9D/y3Yoft923z+zEOpHQDNvzQWAmqAIwq2P0N6evS9RUDGcqKBcl04Ex3kffoOWutDaFzPAOAKQCGnxVR0QF0NisfwYc0wgrxQiRHOdDMhGAwjgxJUZocaKAgWEm56TBWru/OQlfQxznnNaOt2+cZz6+cmkczY3uz5yYGowGdkDt0u7DSd1CZMuWLdiwYQPC1ezntWvXYvv27aMes2bNGtx1113YvXs3+vr6cMstt+Dcc88d9ZhyuYxMJmP7RxDE3ETOOoWIu8lY3edi3BXDEdm+M23mn65f2+Ta4PdqEZTKSo3QjO4QJON+CEyJLyoV/PTOXUiUrbX38yG8sG0IsqAfM5HQDDvHxhnTZzd6o927WM3z6D+YMauEeA9HpLUxaHt/zWHOzBFReAE8Xy1TZh0R1e6IJBN+aNUSWwEapCIzq8Ynon9Iv14wICAS8k5NvPjchbjk3IVYc1QSV1yw1PM1xNTga7LcOXbg4ExRtxDJZDJYssSKI3IcB0EQMDxc+w/D29/+dqxYsQLLly9Ha2sr8vk8vvSlL416neuuuw6JRML8t2DBgnqXSBDEmwzZ4YiUJ+GIsOcyckS6e63HViyKgQ/bhUie82EkU/F2RGA5ImyvkYCmIJuX0KxarsOAoDsmOaXqiEygsyobmuGD9tLXgSFLWAhVwSBU1cfAQevLnBmacTgibEO0pB/wa3poRmPa2POjOCKpuB8aX3VioNm6umoCj6G0/vrmhmDNwXUcx+HtZ3Tgn9+/Gm3NUzcQkHAT6Ggyb5e7B0Z55eGhbiEiiiICAfv/pMFgEIWCe6CTwW9+8xvs27cPO3bswODgINasWYO/+7u/G/U6V199NdLptPnvwIEDo76eIIg3L9MXmtGFSA8jROa1hiEE/Ygevwwax+Ehnz6kLZ11CxGZ481QRCLut1ndwWp+RYtmiYPVpywGYHVjVUvlupL9WdjQzGiOiFgVDCI0cJqG4jDjBEX0Db6v6oj4RE53dJg+KHFRg5/THZFA1HqcTVZlHZEc50My7jdzUwRNRYVxREqKmZqD5gb7HkLMDP6WJLhqCK/cM/NCpO7y3YaGBmzdutX2WDabhd9fu+znjjvuwMc//nGsXLkSAPD9738fiUQCIyMjSCaTnscEAgGX4CEIYvaR29qJ7AtvIHXW8QgunJ7EQqcjIg1koEqy57TZ8ZzLCM309OmPRcIi4lF9o23/+3OxfXEXXn1I/xI0kqlgviNZ1aiYiUV88Ik8FMYRMdyENuibPScKaFvRCjyf1humaQBUDVp5fP0b7I6I/W/k4IglenxBHwyZIEBDJWu5H0IkCEXR0Fd1UFoaQ3rXUr/PnD/ClcpmaMYfttbHhmZiTI1zhvMjlfCjIAjmNaWSDOPIfNkSXE0pyvuYDXACD397A8oH+iENpKGWJZvjdbip2xFZv349nnnmGfN+Z2cnyuUyGhoaah4jyzJ6e61R2wcP6n0AFGXiJXgEcTiQRnKTqtB4s6NpGnp//RfkXtmDgXufnrbrKGzVjH5hW0ms+bpC2TYx1vNcWXuyaq4gIZ3Vj+loCdtCBomktWGOeDgiBViluwDAMy3eg5oKUVORUPTN3t+WQrJ6PnY+zXgTVu1CxC5ghtP6c+GQACFgCQYRKmSm5bwQCWJopAylWmHT2sRUu1TDUvJIzsopCbBCxL1R5SGiwglIxQMAU62jMD+LXMUSIkbFDDHzmOEZbeZdkbqFyMaNG5FOp3H77bcDAK6//nqcc845EAQBmUwGkuT+I3D66afj5ptvxo9//GPcdtttuPzyy3HqqaeisbHR9VqCmC1IQ1l0XvtL7LvuDhT3Hprp5cxK1GIZakHf4Cr9I9NzjbLkWVroDM+Uewax9xu3Y+83f+5KbmVxJqv29FpOwbxWu+ORjFkbcDorucp3rdJd/XUcz5niIAAFLVzJ7HEaaG80BQvbQn68Jby1ckRUVcNwRn+uIRGwuUUiNKh5uxBh80NaGq33ZSSysp85+y2Z8xAiQ3wAPA/dTTIdERVy2eojkilaXzybKDQza7Dnicxsf69x5YjcfPPNuPLKK9Ha2oo777wT119/PQC9gub+++93HfOZz3wGl19+Oa655hp89KMfRSKRwM9+9rOpWz1BTAPFXd3mWHJnJ8upQFMUZF/Zg/IsyFafKGzHUCVbHHejMaVQQvbFnVBqjKcH7BUzPFPN4hQiuW2d0GRFH2P/2v7a56uGZvhwALwomGEZQM8PYUnELSEykqmYm7RBiSndtdZYFSKago1LrPUGOpoQDYsQBc7WQr6WI6JpGroO5VGu2D9TxRAinN2pyOYl0+FIxv1m7B/QS3hRcggRtmLG5oi43QpWiLChGYNhLoBE1A+e58zr8uxaAaSLTJdWCs3MGmZTwuq4Aq0XX3wxdu7cic2bN+O0005Dc7M+srmzs9Pz9cFgED/4wQ/wgx/8YNILJYjDhcxsjtI0hGfSm7aj//dPgQv4sOSrf2da4kcSctruPMiZAnwNsbqP773jMeS370NoRQfmX3mB52vY5NLwig7kXtkDwF05w4ZcZGYoHYumaeb5vBJVO1ocQiRmbcDpbAV8wAdO4M35KYYjkrQJkQAwnENEUDEvpcH4zfHPawTPc0jE/CiXWEfEW4g8+vQh/PaPnWhtCuLrnzrenDxrOCgyLyBbkBCP6tc2wjKA7ohwZUaIQAXHiALdEbEqHVubQsxz7t9DmxDxyCEY5gJIVl0h3mddV2OuOVxQAIjgeaAhObOtxAmLQHuD3tdG046c0IxBR0cHLrroIlOEEMSbDXZjq/RPvRApdup5U1pZQqVX31Sl4RzKPUfO+APZkbvBDnerB+MzKO/vq/ka9hp/3lOBJuqbv1Mcsq6KNOjdd0gtVkzXRvAo3W13OCJ+n4BwSN9YRzIVcBxnc0XY9u4GZi8RRUWJeV+Bdj0UnUr4bY6IWmOa8Evb9N+D3oGSOYUWAOSqcCmoPB58osd8fDhjvSaV8INzhGZEiREi0ZBZMQPoPUTM58ZwRDgvR4QPmK4Q68SwQmQgrYd6GpMBCAINfJ8t8H4f/C1JAHovEW0Gczfpt4IgHMgZdmNLj7vMciyUnLUBKvky5EwB+66/A/tv+C3yrx8Z5epK2iFERvI1XulGU1XTDVDLEjRV9XwdW+XSX+bNvh3OvJF6hAgrasR4BJqmmaGZZNzv2WQrVZ2fMpKpQFU1s/QVsByRaJhxDJhKFsPqFhMR0/FKxv0os8mqJe8cETZ0UixZm4ORI1KBgD37LeeHdURSCT3sZL5XTYXPyN/jOPTnFezr0UVjOCQgErbetzP8BNi7qXolqw5zASthl61kqlhrMt7CisVxj3dLzCT+ebpI1hQVld6JNwucLCRECMIB64hoFdlduTHp81sbp1ooodR5yPy2XjpCkmNdjsg4PiO1WAEYccf2x2BhQzN5TkSpqlc0hxCRs2MLEWcPkXRWQqGaROlMVDVoSFarSBQN2bwEIep2RGwbOdtdtTq4zd9qDdFLxf2osI6IRyJuoSgjm7ceL1aHx2mKAq76O1LmeHQdypt5IUazMOMarCMiQENArSaOBv343i3bzfd91JKErVIotLjNtR72MWdoRgUwwvmRSuifk+BnJvAyVTNytd/KyqUJELOL4CxJWB1/MT5BvMlxtRXvT0NMRKfs/Ow3eKVQNvMOAExquuzhxJUjMg5HxDnbQi2VPfNk2J9DnvOhoukbmlqRoGmauYnaPs9c0bMnAnsuvWKmdn6IAZvPMDhSRohxDIqc4Ygwm37Inf/gb7OESDLuhwxr49ck2fV6tqIFsBwRVrRUIECSNRzsL2B+W8ThiPjB+ew5IiFNv85IhUMW+u2O1jDe+y6rUzYAhFctQMcnLoTUNwLwPALzGhBcYPWHcYZmMpwfCsebFUaCTzRH5fFMFaUMQ4iQIzLbcCWsrl85I+sgIUIQDhSHEJEG0sDyjik5t6ao+hRY41qFEjTZ2pCOGCHiyhEZjxCxb7a1ylhZFyPHiahwvN7fQtM3cc7vg6YorlwLaShj5mV4nUuMh9Hl6KjqRWPSEkdDI2UsilsTavNVIcKGdJxNxgDA32r1WdKFiGVCe/2se/vtIq1QdUTYz8goAd7XnfcUInnGEQlqitmcLKfpxy1oD+NzHzoGYUc4iuM4hJfNA5bNgxfO0MwwFzCvCcDWv0RgRJYMDq1NQTPURcweAvOb0XDuOgQ6mhBcOHN5nxSaIQgGVZJdG6M0hQmrSr5oNovS75egMA2njhgh4swRGUeyqpK3C4daZaxGjogMDmUIkJj8CrWib3TsZ2fgFZ7pfKPfvC3GI3j1dSsevqjD2+1qSFgb5+BIGYkNq+Fva8D+aBN6uRA4DrbNnPdyRNjQTCIAmWMdEffP+tBADUeEyScpV/9sG7kew9XQTDQswu8TbEmjUY0J81Q/v2NWpFwipB44h8s0xFm5LwAgMo6JqDBChOMpLDNLEcIBNL59PaLHLplS13e8kBAhCAY2f8NgKjusOvtmqIWyLVShHgFCRFNV1+c0PkfEGZrxdkQM1yXP+QCOg8QxbkI1VOHVh8RLiHTvseLf3TkNOzv117Q0BjGvZfQcEQAYSlfgb01h0VWX4bHEUoDjEAoKZmktUMMRYUMzMT+UsRwRhxAxHRHmMzLyTPZ356GqGkay+nOphDtpNMYKkaqL05CYWAktJ/AA835H+ABWLI6hKWXkiHgLEQUcVpEQIUaBQjMEwcBWtBhMpSMiOzZwJV+ylz0eAUJEyRZtyaaAnjOiqRo43nuyqu34OkIzqmyFXHLVDbTCbOJGO3fn5wkA0qC7l0hYtTbk2x/sNpd/4jENNafBsjkiQ0wZbb6gb7JsxQzgzhER4mEITCO2RMwHhbmW6pUjMmAXaYYjotgcEf33petQHsPpijlQzkgaZX+fYpp1nCFEkhMVIhwH3u8zRdFl7zsWqTWLzM/PWa1jIIPHUUsoP4SoDTkiBMHAlu4aSIMZaOrUlPA6nQSlULJtzGMJETlbQNeP78Whnz9Ss+x1vIy3PNmzQkZVR+2SantpHY6IrWIG+oYvsUJkFEek2DfiWJqGcDVhswIevRlLAJx4TO1xE4moH4Kgb7KGEFFVDYWqOHCGN9jurwAQaLPP4RJFHgFmiJzzZ62qGvpcyapuR6RcdYYkWcP2XSPm42a7+VqOCIxusBPP1WATVmPzG20ijk2SZWltjSAWmbmBasTsh4QIQTA4E1UBfcOQR8bXsKve8yv5ki1UMZYQOfTzR1Hc2Y3sS7tQ2Nk96fX0/vZx7P2325B/rf5W9s6KGevx+j4jpTB2joi9YkZEIubTk1WraGaOiFuIlPrsDlaxJCNQnYjLNhRrTAawcF4EteB5zmzWZQiRQtESMWzFDOAeRMfmh5jHxK3KGyPPxWAoXYYk20WhV45IhcmVefk1q8tsQ1VgsIKAFSKFSYZmAJgOD+cTXTkFrBNjIIPDwho5OARhQEKEIBjYDdBX7ToITF2rd88ckTqTVTVN0+fgTNGa5EwBmWdeg5IvYeiRF8dxHNMcjGnrXm+eSD05IoqjdPfktU3ejojXkLts3uZg5QoyAtXKEXYTHy0sY2DkiRRKCoolGbmCJR6cTdCcyapeQiTOJMDKjj4ifQPuxFuvHBF2cN7WN0bM2145IiFYv09FToQocrbeJ+MlecZaCJEgGs5d5wrDeQsR3tZGniC8ICFCEAzsxhZaYjVzmqqEVdkhRDRZsfWTYHuKOCl3OeZBTDJaJA9buRTlA/2eOQtesF1V2T4T9fYSqSdHhA1h5TkRSxfGILATZ40cEebzHOGqG7GqQslaa8nlKvBVhUiZcVVOXDP2FHC2cmYoXUGecUScG7rgCM2wiaoG8YTliEhl++ftrJgBGEeE+Yz8kQC89JMVmvEOkRQ5UW94Nob4Go3EKaux5Bv/gIa3neB6rpYj0tJIg+6I0SEhQhAMbPJjaGm7eXuqEla9qnJYRnNEclv32s9Vo+y1XiRGUGiKinJX/yivtmBbrwcXMkJkgo6IZ2iGERgFTkRzQxACUz7qlSPSw1v9QCoDVuVMIW29xhcOoDEZwOnrWrBk/tghg0ZHwmp+NEfEFZqx54gAQDIRMJuaKQ4h0ttfQJtaAM8keho5IhLzGYUTIbz1pFbXua1kVW/HowjBfM1kqCVkPIUIx9sm/BKEFyRECIKBTZJkm2JNdtM3zzNGQudoQiT/ql2I1BqaVi/OvJdine3lWcExMSFiX/fYoRldiPABa6OXq23hperPSwVwiBEiQ/utct3CiPWZR1NhXPv5E/H+S5bV5Qw0OJqa5QtWOCXiqJrhBN7s6CrEwp7dYlNMd1WnA9X8yqv4u/JOXFzpRDCgb+pGYqzEfGa+sB/vfvsis2zWwOjnMZYjMl14CREFHFoaSIgQo0NChCAYjBwRPhywN3AaJWQykfPXopYQqfQOu4ZSsR1aJ7QWhxApVSfijnlcNUeEE3j4261v/fUkq+oD7xw5Il6hGUawceEQggEBvpD186hUN2bDwSpAxAhnbczDe6zptyUmB8cZPhkLVogMjpSRGyVZFQDip6wCOCD5ljWe50smAmYvEbah2dBIGQ0junharGbRnNIFQ7GkQNM0yKwQiQYRDAj4h79dbp037odP1M/LewgRBRwq4M3wzXTAVusYaIIAv99bGBGEAQkRgqiiaZoZOhFjYXA8U6UxBSOyNVXz7ARqe00NIeIMywC1W6PXizOno9R5qK5SXqNqRg4G8bvHDgLV1t/15IiohbIrt0UtuZ0diXGmYk16CMXHJINW8mVomgatKsYKnIhKQ9I65wFLVJWz1mfuC49vI7bniIwemgGA5otOx7JvfRgN55zoeb5U3G91V2V+px58/AAi1QoXHkCiqrlUVUNFUm19RILV4XtHLYnjiguXoKUxiIvOWWA+7yUIihAAjpuS0EwtOMG9nfAeayEIJ/RbQhBVtLJkJo4KsTA4kRUik3dE1FIZGKP3Ry0hUjrgzt+YbLjI6Ygo+RKk/jT8TLWQ65iyBLW6+R8sAo9uOoilmogEpLom8DrzQwBvQVWpip0KeDQ06SEXPyMipGJFD+lUfy4FTsTi5U3o6w2iRSshlM1AKZYhhAL2sEZ0fGECe1OzCkJB609mreoT58A9lmTcj87q9z+uKkSG02W8srkH65nXJQSm2qWkQCnp9T4yOIQi1prOOLkNZ5xsn5rrFSIxmplNZ2jGS3Sw82cIohbkiBBEFTZsIsZCDkdk8kKETVT1mksCAJrsfR02d8Vos61OcWgGGD1PpPtQHj++ySrzzXP6hptRqqGGijxm5Y1XOEkpVVxOjFoNzeQ50Rw+549Y3+alkmQL3xQ4Ee2tYfQG9A6eHIDinoMAAJnJpQnGxidE/D4BsYi+mbqSVSdQBhsMCFCrv1d8VZQ+9NcehGS7GIvxlhAplGSgmpxbhuDpxLB4JauaQmQ6QzOiezvxBamRGTE2JEQIogorFIR4GGCt5ikQIqzQ8eoxAdQOAbG5K2JMdwicjcHGg6aoVvUL8z5Lnd5CZCRTwff+dxu0HsuZqST0+SEldhjdGOLIyxGBotpKmFVZAVctzy1wIpLVRl3BqCVElJJk+3kVICIaElFqthKM068d0F9bZIXI+HtaGHkiI9kK0llLMIwlCGoi6J+XAA2KomLTi322VuwAENGsz6NYUoDq51HheITHEEAcz7lckWK198i0hmY8BJA/REKEGBsSIgRRxe6IhO0zYKbCEWG+wdcUIh6hGWfuitFKfDI5InK2YM6LCS+bZ4qR0n7vhNWXXxtCoaSgQ7XCL+f/v+ORivvNb9vA2OLIU4jA/l5sPUTgQyKub2Yhxs3QKpKjxNeHSFhEYEm7mYKS39mjv5ZpHOaPjn8jNvpgaBqwr0d//zzPmZUt44VNJu3qzqFcURHX7M3NwqwQKUrgZf1+PY4I4A7PFCBCFDjPBNupwiskFBxnTg4xNyEhQhBV2PCH4ArNTD5Z1dZDpKHGNFJFdc21UR25K3y1LFSTxg6F1IINy/iak/Al9YTQWu3bd+3T+3IYQoQTeIQWteCMU9psbdNrCQ2v59mqpPLBQXT9+F703f2kbfBggRORiOmbWSRmiQit4g7NRMIi2hck0c9VBcvAsC6MypbIGW/VDAAsnGf1G5EkXZBGw+KEG4OxuRS79+iVUDGHEAkqTGv2bAVcVTSWuTqFiCNfo8iJSE6ymdmY1/QQImw+C0HUgoQIQVRhN0khGtJzMap/t6fCEWG/wWfE2rkKTtGjOHJX2M1UnWDCKitExGQEQiRons9LdO3el0VYk9BQDSEEFrSA94l460ktqPCMIzKGEMkMWNf1N1oTWYf+9AKKO7uRfnIr8ls7zccLnIikIUSifkjGD0SSXb1GIiER89si2M/rwkHPE+kBJ1mburPpWD0sbHfPo5lMm3Q2gXPvPr1RnjM042dyRspMJ9oKeNewPS+cvUSKnGCrAJoOvIQIJasS9UBChCCqsImUQjgAjuMsV2SKQzN9Jc6WW8HiDM/YnJp4xHRE9DVPUIgwzcfEZFQXXsY5HQ3HhkbKGEpXbGEZo/19NOIzy2sBoDjiMTRQ09D3uyew/wd3o/tFa7ie0GAJEbYqKP9Gl3m7wInm5NZIyGfOm+Fk2e2IhES0N4fQLVrryb7RDb9mfZ4TEiIeg/EmnB8CQGScoP1Vp8npiPgkZshd1vp51OuIOCtYihCRnMZEVcC7kVqtLq8EwUJChCCqsJ1K+XDVsajmTkx11Ux3VjUTCJ04K2ec1TxT7Yj4XELE3v119359Jk2HwggRpv19MG51NM0NuUt4K73DSG/ajvK+XrRI1nV3DDLvkylrLjOiRAsFIQi6CxIJi5Cqs2J4WbG14y9ARCgowufjoTZZTdZKfSN2IVKjWmk0wiHR1cV0Mo6In6kkqVQ7xDqFiMD0VpEYgVzhhLpyU9zJqu73MNV4OSK1urwSBAsJEYKowlZXmOPOqxUOUxKaMYbM8Rz2Dcko1Wjj43JEHNU8bOtwZYIJq2zzMTY047weYOWHzGcckeBiq3dFOGUJES9HxFZ6zLBjoEbeDVPKywqkgJ+HVHWRBFWxOSJaKGAKloaOBIyfVnEwhwAzu2W0Hh+jscgxyj46CUeErSQRoULQVERgz/XhSpb4kArWz1j1ieD5sfM8nAKgsT3uOZ9mKjH+X7E9Ro4IUQckRAiiis0RCfmhKBoK5er4+JJU67C60FQNxd4RAEBWCKKrr1TbEXHkaDireXjWEZlgLxHJcEQ4QIxHHI6I/Zy792fh0xS0aPrG729rsImhWKMVuqh4DPXzarxWAl/z/bP4GLeF4zgo1c1O1FQzR6QM3ladMb89ikJV5Km5IgLQP09FEG0JyOPBmScyVgntaASZBE5R0xDVPH63CiVTkNnEpr8+R8eZrPqhv19ja1c/HXA8Zy95BzkiRH2QECGIKsaGyQf94Hge+3pyqFS/nFcqk6uakYez4KsC45DiQ6ms2MpeWUbLEZEDATzzmjUJeMI5IlUhIkT1MmWbEGGchmJJRtehAtrUovnHwsgPMUi2xKzzenVO9VhjEGrNHBmWEOO2AIDKfOuWhvX3kK9WzBjMbwubzdZ8lTKC1dCM5p94T4uFHXYhEp1Ef4wAc6wA1RWWAQAoKvxVX4cVclydjo4zTCJEpleEGPCO61KLd6IeSIgQRBVjwzSSQQeGylCrVRrcGK3Zx4IdWDfI62GQepNVWUfkrr/24uU9Vp5FPTkimqIi/cxrKOzqrt5XTDdBTOobrMC0PmeFyN4DOWgakNKs6wQ6mmznb2yzhIjmNcDOq5sq9MTL0ZDBIeoQImA3Nqa9O5vAuaA9glxV5PGAFfaYYFgGcCesTiZHhHUrRGjeQgRWU7MKkzxcb7ItKwA4vwh+EiJsPDgFEDkiRD2QECEIVJuGVTd1Iz9kYLg0ZUIk122NpR+qTollHZEK879izRwRnsPTr2VsIY16hMjIE6+g77ePo/um+yANZfVeIVWnR6z2DxEiliPCuhoHDul5IUlGiPiYslsASKZC5vr5iluIeDkiuxsXoDyGI1LgRCTi9m/ymsc37AJ8NiGSiPmhhd0dVPnAxKtGomGf2WoemJwQYV0DEaqtdFdMWbkoSVH/PWAn7wp1JtuyAoDN/5luXELEI4GVIJyQECEIVLtvVhuJGY7I4HAZiiFE6phKOxq5LkuIGI5IL29tlt289Y27liNSEvwAx6HMJLnWE5rJvrxbv6FqKHcPOCpm9Ov2M6YF64hkc/q39aRqbZZOIcLzHCqCviafLLnmxrBr/KV/OX4ZOgqZY1eP6YjkYfUQMeB87m/2BU505WxEm2Ou19W7iddiAeOKTKZ81+aIaJqtq2pgfrN5OyHq4tenWr8PvnB9IRb2GqzInG7cjgiFZoixISFCELBvlpYjYoVm+EkKEalvxLx9zPoFOH1dC069aC3aP3A+Xj7qeBzkrRAEW76rqaopDEbkaht2tpPpGEJETudR7rLKYeWRnJWoCkBM6Rv2Lfftt87JOCLZfFWIGI4Iz5suCovi0zf5gCYjX7RXgLA5Dhnej0oqiXjUj4rDEUlzPrCfsj5nxi48BI8has7QDAA0z0+6XifWuYnX4qQ1+hybcFDw7C1SL+xm7cwRCS5ghEh1Aq8flhDx15nrYbvG4XREfJQjQowf+i0hCNhDHGaOyHDJdER4aNA0bUItsjVNA4b1EtgM58OSpSmcfJy14Qg9POQ91rA51hFR8iXTqTESMNmQxlihmfz2fbb70kgOQsXa+MRUDMPpMg4OVlABDz9UVJhmZ5m8BGgaktXwga8hCk5wf3/RAn6gBAgABntziC6xZumwlT0lCJiXCCAaEaFynHlNAOjlwlBRRKp6rQLnM9u7GwgeeR4FTkRH2P542+IG9P/V/rqJzJlhOenYRrQ1h5CM+xEKTsYRYUMzmhWa4XkE2q2hfTFO/z1gy48D0fpEBW9zRCg0Q8xuyBEhCLh7iCiKhqF0GSorPCaYJ6JkixCqbcYHuSAaU/aNoakhCAXec22cbcx9IgdO5FGuvn4sR8QpROThnFltAujNzPYc0O8XqjkrUpYNzcgIQzbFgq/Re0YOW8473Je1PWesUQYHGRwakn5Ew25RNcQHMMBZnw3bVdW8jkeyppcjEmxwuza+SW7IHMdhQXvEtaZxn4fNEdFUxKH/boiJsD71uUq4mmQbYByRpSusZm31XmNGhQg5IkQdkBAhCNg3dD4cwHCmDFWFGZoB3B1P68VWMcMFXB0uGxJ+KBx7HWvjkTPMJFpOxMJ5UTQ3BM38itEcEVWSUdjZbXtMHslZjdWgOyJ7D+j3jd4bQkUyG7hl8xISo+SHmI/HrDyETH/O9pyRrFqCAHAcUomAOQW2zFl/goa4AAZ4a9NUgwFX8y6/R55HAW4hIsTcoZPJ5ohMFezm7IdqlheL8QhE5nMMq7pAMTrDagAWLkqO+xozK0TIESHGhoQIQcBe2SGEAhgc1u8rjBBRx5jAm3t1L7JbdruSNVkhkvaFEI/av1GHgqLtOppUyxHxYfH8KFJxv1n6qxTKrusZFHd2m1N7DXQhogsFzidCiAZNR4St4skP56BpGrJ5yQzLAICvyVuIBBPWBups8264TaXq+RuSAUSrrgKbsDrEB9HJW0mm+WTSdR2/xzRXZx8RALYN3WAic2amA7ZqJqxZPx8+5LcllgrVqcGBqhvFB+qfnssKAH4GhQjliBD1QEKEIODOERmoChHWEZFKsus4g/xr+3Dw1odw6PaHUXS4EKwQUeIx12YS8PN2IcI6Io7QzOKOKBoSfnNTh6K6xAa7JpPqNeVMHtKQ7oCIySgURcP+HntoBgDe2N6PYkmBomijlu4aRFKWA1FKW2tWJRlaRV+fUXbckPAjFtGvleF0cSCBwxAXQLcQxa/8y/Ar/zJozVa+hEHAI1mzwIlIOMQdJwquDXi2CBFWJKxqt9bEBwP6uqvJ0kYfkUDVERHC9a8/uMhq5x5a0j7KK6cWyhEhJgIJEYKAu2pmYFhPsGQFQrlcW4j0/N9D5u3sS7tszxUODlnnbk66jg34hPpyRODDkvlRpBIBWzO0Wnki0kDGvB1aVt2MNJjCxZeKoqu3AEnWHRWV2aj3vjHAVMywoRnvHBFWiLBt3lmBZ6y5IRkwQymbxDZsE1J40LcAlapQ6RKi6BKirkRVAAg6Ek4VcGhoiaLRY6CbGLc3Q2OHBc4k7PyVpMDMwamGjoSqm+OXK1jQHkaQqzoi4xBSoUWtWPCZv8XCf7kUgfb68kqmAudsGcoRIeqBhAhBwJ6syoeDliPCuBfloncHTE1RbYmszpi8VHVEChAQb3YnUQYCPOSaOSKWENFCQTQ1BJBK+G0lvLXyRNSytV5/m3szElNRMz8EABYstV5zaP8IMjlH6S4AX4O7PwcAiGxnVqYBFyuSyqYjEoAg8AgHBQzzATzgX4jXRb3KpqXROk8i5k4KDcXsYqIAEevXNnuGLMS4PU9kNjoibM8WIxHXDCtJMq7+0CoImhWaGQ/BBS0IzHO7StMJJ9KsGWL8kBAhCDhyRMJ+zxyRSo3QTGlfr/1cTHmsnMnrA8wA9PMhNKXc8fqAX6gZmikNW/kWzfOT4DgODYmALbfCq3Mpuw7OJ3oKCF8qZuaHAEBzR9K8LVQq6DK6qlaTVYVYuOb0Wp6pmhEkCfmC5FpbiRMRDllj7KMe1SdHLbFCP6mE28EIOspX85yIk4713mwFhyPCz5JkVTZvgg29mY5I1Fq31J92PT+bcTogFJoh6oGECEHAPg+FZ0Izah2hmfy2Ttt9dvMtdw+Yt3v5kKtiBgB8Im8PzTDVOeVqvoUEHgsW6pt0KuFHkQ3N1HBEjNwM3i96NiFjK2Z8IoemeVbYJazJ5tRdY1ZLrfwQwO4ChSCjs1sXMawjUoSABkZcRD3apL/t1HYsWxjDsoUxnHiM28VxNjTTggG0Nnl3DnWGZmaNI8JszsbPCLDWxw4glAbSrudnMzzjiHCiMKG+O8TcgwJ4BAFANYa18RxkQUA6q3+jtzkiNYRIztGrgxUG5S5LiPRxIbzVQ4jwPAfexwPVJbCOiFrQO20UOQGL5+uuRsrhiNTKETFCM1zAB5+HEJHCQfQP6a3nF86Lws9s3CFNxo79OSTqqJgBACHMCBFNwc7ODI5ZkbQ3M+ME2yh6L0ekuSGIL3x0Tc3rOIe3RZvc78tAjM1SIVIjXGEkqQpMxU9l0MrzmS3rHw02R4TCMkS9kCNCELDyLPhgAEMj1ubLOiKyhxCpDKRt7dsBRzjC4Yg4m5kZCIylbQgRTdPAS/paShCweL6e8xAMCFD91qakMi3ZbeuohmZ4v2gbpmYwKFkbxYJ5EdsE3rAmY3Ck7EhUrS1E2LBBUJPxxl59A1UcyaoNCet1Tkck4Ofh843+J8kZGmryaOVuYAvNcJMbejeV1ApXGDkirLvEhma8mrnNNtj3RomqRL2MS4hs3boV69evRyqVwlVXXVWzf4HB17/+dXAc5/r3l7/8ZTJrJogpxwjNCGE/+oeYxFXGavZyRJydS/VzuR2RCniUQuGaw9IEP2PXG0JEkiFU/x+rCCLiUWsjYsMOUtretwMANFVjQjM+Pe+Abc3OcehmDutoDdtCAqFqOCZRpxDheN78Rh+Egs7uHCoVxfZZlDjR7og42rI773tex7G5xRpHcUSYZFU+4AfHz44wgbOyxMBwPMQjODRjEyKUH0LUSd1CpFwu44ILLsC6deuwefNmbN++Hbfeeuuox3zpS1/C8PCw+W/Lli1obm7GCSecMNl1E8SUoakq1JK+4fLhIHbvtypJYswYeslDiLAbhYHhriiFktnFtI8PYmFH7U1T8DOOSLV8l93EZdG+SRtTcwGgNGTvZArA1luEC/jA8RzEhHWMmIigp986f0drGLxPBFcNfRiNtkJMwy1nqMP1Hqo9PkKa3n9kb1fOHZphc0Qi9g3Z2ZTMC47nwDGflTDKmlixNps2cY7nPOf1mKEZVogMHrlChJqZEfVStxB54IEHkE6nceONN2LZsmW49tprccstt4x6TDAYRDKZNP/913/9Fz772c8ikfDuRUAQM4FaqsAY+yqEAnh9j/XHv4lJhJQr7s6qbBjG2CiUot7ttNw9aD7Xx4Vx9obajaVEZnNVq51V2Sm4xnRbg1CjVQVTHnYLEbZyx8ir8DHhGTEVRXevVbExr0V/n0Z4JuQhRIQxBq4ZeSJBKOA0DW/szUApWI5KCcLojkikvo2LzRNhN23XemapEAG8wxZeyapKruR6fjZjD82QI0LUR92SdcuWLdiwYQPCYf1/7rVr12L79u11X6inpwd333039u7dO+rryuUyymVmbHgmM8qrCWLysM6DFvBh3259Y29vDiESscSHVHE7ImwOhK8xrlfJqBrUsoTe16wOq4VYDGtXpVzHG7BCRKlep8w2BnMkaSZTIRQhIAQF5aEc+odKaG5g5rSUWSGin1tMxgAc1G+noujZqwuRhoQ1TVaMhiAPZRGqiomQZr3/sWaWsCW8QegJqyfKrCMi2nNEHMKjntAMoOeJGP03RhMivE9EaFk7irsPIryio65zHy68whZCyC1EWI44IVIjBEUQTup2RDKZDJYsWWLe5zgOgiBgeHh4lKMsfvzjH+OKK65ANFrbngaA6667DolEwvy3YMGCepdIEJ7kt+9D+unttmoUFrYhWFbmzd5kRy2N2wSCLI3uiIhMrw61UMbBbZYQWbF+kWuAG4sYYIRI9TrFEcux4BybUGMygBynb9xCqYSv/ceL2PKa1cGVLQvlqgmeIhPOUUJhFEv6dea1Ws6BsQly0PNEjFwRQA9bjQZbORPUFOw5kIVcMFrlAxLP27qlunNE6tu4OEaUec2UYZn3kXdiwacuQdOFp9V17sOFyy3gOPPnxIf8AO8RugnWJ9RmEvZ9kSNC1EvdQkQURQQC9tLDYDCIQqFQ4wgLRVHwk5/8BFdeeeWYr7366quRTqfNfwcOHKh3iQThotQ1gJ5bHkDfnU8g8+JOz9ewjshgwerhsWppAgLbBdMjNGMcywf9NsegnClAGBwBAMjgsG7jslHX6Q+4QzPlrOUmcEH7/3trVqYgVf9/FKHBryo2IWJ3RKqhGaY9e0a0zmcTIszGHtFkM1eEC/jGjPnzTAv1AGRIsma2ey9BQCoRtIkxp/Co1xExPmdOFMZ2aXwigotaZ02iqoHTLeCDPrPnBsdxnmEwPjg7WtSPBuWIEBOhbiHS0NCA/v5+22PZbBZ+/9h24WOPPYampiasXr16zNcGAgHE43HbP4KYKOknXzVv99/1pOdrWFfjYMYSG0ctjsPHVLPIXqEZQ4iEA7ZZJulDaaSqrdELkShCY2yyPubbrlpNNGVntghh+yYUCYlYeWybeT+qSShVLBFlyxGpftOOHb8M4aPmI3zUfHTFmsznO1rcjgigJ6waoZl6RsmzazRG2xufT4kTkErY/1bEIhNzRBredgICHU1ofOcpR2xlhtMt4B1zcLzCM8KR0FmVckSICVC3EFm/fj2eeeYZ835nZyfK5TIaGsYeqPSb3/wGl1xyycRWSMxqcgUJA0PefSwAPRF0+C9bUNjdcxhXZVFkEjmVgPc3SjbP41BO38znt4URjfjsuRuO0I6mamZYRwgHbTkShQMDZgcSeYxwJAD4AwKMs6vV60hMoqKXEGCrYKKahAoTOrKFZqrvgQ/40PGxd6HjY+9C96AlVDraLCHCVsZENAnBamimHiHC9hIJaHqOiSDp1ynDXroLAKGgYItAeDU48yJ81Hws/Nx7kNq4tq7Xz0Z4h4By5n+IHkKkVnv92QTliBAToW4hsnHjRqTTadx+++0AgOuvvx7nnHMOBEFAJpOBJHkPBAOABx98EGedddbkV0vMKkYyFXztP17GV//jJWzfNeL5mqFHXsTAvU+j5yd/tLVRn2ryRRl/efYQDvbZQ4XsrJai4P2H3NaArNo6feVSPYzBOiKKpNqPK1eAap8PPuS3OQLSIStMwjmGr3mhz5vR/3c0cllkZnic3yMXwilEymXGEfEIzbD0VD8njgPamMog9pt4g1Y2/0DUJ0TsyaoBMDNzHKW7+rU5WzimXkfkzYDTLXA2K/P6vI+EWTM8OSLEBBhXjsjNN9+MK6+8Eq2trbjzzjtx/fXXA9AraO6//37P43bv3o2enh6sX79+alZMzCgDQyUUq8Pfnnm5H/miDE0DXn3dO2k5/7qe46NJMir97p4bANA/WMKTm3uRL3q3UK+H39zfiTvu3Yvv/3Q7FMXakDVG/FREbyHi7P4JAMsX6YmnPo/cDfM+c5zuiDCbRzU/BIDnnBcnQWbwnTFrRmPOH4h5OCJMeWpUk1FicljY0Myre7O241RVMwVbS2PQ1s2UzRFpVEd3ZJywoamGEGeGZwC9RX1D0r2RsuJjbgkRR46IMzTjEJ6cTwQnzP6NnWd+T+r5nSEIYJyzZi6++GLs3LkTmzdvxmmnnYbm5mYAepimFsuWLYMsT3yDIWYPL2wdxM2/egPJuB9f/eRavLDV6pMxkqm4Xq+WJVQOWs6A7NEBVFU1/Odt29E/VMbOziw++J7l416Xqmp4ZYd+nZGshL7BEtqreQ9CydrMKzV0t31CrP7H3uiAyn7DUx2hGcU2sdeeIyJmrZBQgOn5UQvbBN5qQzONWXsw4W7cxXYOjWoSyowQ0RhH5LntI1hXlBGuvqf+oRIkWXdyOlrt52UdkSZtfEKE/cbeGOIQLDOOCNyOCGAkqOq5MJE6k1XfDDhzW5yhGWeOyJFQMQMAgbYGpM46HuVDQ0hsOHqml0McIYz7K0hHRwc6OmZXTT5xeHhpmy48RjIV3HHvXuzvsYSFMSSOpdTVb4YuAEDxECKDw2Wzpfrerqzr+XroOlRApJDDudIh7BQS6Okror0lDE3TwDHXVxXV8/hKn+XmGCWxfr8uWtgOmE4hwgqYVzvzOPUUazNhazQiLWMnXPv9PBSO1xurVdfJlXVxp4BDKObexF2hGVuyqiX+JfBIZys2IWLgnFzL5iaw7d2FyOhlsoDdEUn69ZkzBs727gbHrkrhjc4MFrRHkIgdGZvtVOCumnGGZpxCZPaHZQya3rVhppdAHGHMHS+UGJPtO0dwsL+IM05uhSi63YNDA1YVB+uGAN6OSGlfr+2+nHGXeh84ZImTkUxFFw/jHB3+RmcGp0uHsFzNYKmaxa6uNLCm0Zqoay7AXX6ryYo5D6YYDKHE6f9L+I34NuuIOIQMG9LZ019BsqsAL8kRax+7k3DQL6DkcET4at5VCQJaPGbUCNGQnuShaS5HhA3NVMAjm5dg9HUdTlufi1Mc8OEgwHOAqtn8o/HmiEQFezM0PUfEvZmee3o7jj0qiaaG4JwaGe/KEQmN5YgcOUKEIMYLTd8lAOgi4Ic/ew2/+WMn7nusy/W8qmroHaidbDqSrUBV7UMQS/v7bPe9QjPdhyxxUq6oZpOt8fDG3jTi1W/vAjSU9urdQ+URu8OieTgi5Z5BMzk0E7FkRKCaN8ExZR1G7oaBM6Tzwi53q/UKeCQa6klW5c3QDFftqCYaQoQTPIflcQJv5hIYjogxiFJhRJjE8cjmLXdimBGNqbh9g+N4ztP9qEuIsOW7nGJrhib7re6ttutxHNpbwvB5CN83M7yzfNfpiMRIiBBzh7n1fz9RkwMH82ZH0Qce73Y9P5KpoCJ5hzYAQFE05ArWxrPnQAZDO+znkTNuIdJ1yP7YsIezMhqqqmFnZwZBpkJD7NX73UjOYXAeQoR1bYZDVi6HGZphN0hVtYktxTbQTcSWXRndTWDICX6IdfS68DM5IpyqQlMUiGq1wyonIBT0PocRnglDhqaokBV9fSVmxosEAZmc5ZAMpy0B5eztAbg3QaBOIeL36Q4NAEGSEOeZn8kordjnIq7QjDNZ1fF5kxAh3syQECEA6EKC5VB/seZ9tjumKFi32fDMH+/diYBkFxVejkjXIXu4ht0k66G7t4BCUbFVaDTm05AkFdKw3RHhqht7uaLg9T36a1jXZiDACJHqN1bWEeGh2cSYs+xXVgDVZ89zKPnq64YZNHJEoOeXGLNUAKDMiVaoyIGRsMoDiEA2wzMSU/pb4fTQjAEbmkl5JJB69rCoQ4hwPGcmrKrFCpoC1u9UIDn65N65hruh2eh9RJzlvQTxZoKEyBymXFFMK79Qslc2bdkxZLvP5odccPZ8LF8Uw+plCZxxitXd0xAimqZBOzTgup7iyBEplmQMDNuFh1euyWi8sTcDQVPhhyUQWtQiDnalURywD0zkVD108V8/24Eb/2877rh3j+mIcKKAft7abI1QAZusKmiaLQ9DyrOOiL6xFDT7BiMF63MCbFUzsOfTyDXKjgFATLAlvFYvEalkCQ8JdiFifMZ+H4+wh9Pi7YjU9z6MhFWlWEbCZwmRcMPYJcxzibGqZriAz94unYQI8SaGhMgc5ZUdw/jid17Av/3ny5AkFQVHbsbL22sLkaOWxHHVR9bgMx88Gm3N1gZlbHD5gozGshUW0ap2vVqq2Bpt9fTZXRfA/m3di+EnXkHvnU+YjsEbe9O2sAyg/1L3bzuA8qDdEdGFhIqdnbpA2bG9D9KgfjswvwnlqhYTBQ6C4fQwvRt4aCgxJansLBhDiGRle2hGrXMD948iRBTfaELEu4RXKbGhGR5ZNjRT/TmlEn7PBFEh6nYvnC3ma2GEGNRiBRFNv6YGIN5IQoTFOYfFmayqz5uxfndIiBBvZkiIzEF6B4r475/vQLGkoHeghJ37Mig6mont7cohk7M2MzY0w4qPVJhHuLrhjGT11/cNldCmWhtpOp4yb7N5Il0H3aGa0XJEKr3DGLhnEzJPb8fIU9ugaRp27cvawjLma/cehDRszxERoGFopGxWFCfyllAJLmo1wy5+psEX64g4QzMSMwumwusbi9EQzTymjq6qgB6akZn/HaW09flpgdqbkFCjl4jR4l0CB43jTEekWJJNMZWMe5/XOXCNDwVsn8NomCEGTUOgVB14x4lYd1xzXcfPFdyOiFvo2YTIEdBVlSAmCgmROUa5ouDHd7xueyxfkF2hGU3TXRMDo2ImEhbNttxqqYLgr+7HlaXt6FBypiPSN1BEc7UrZ4bzoUe1/siyeSLO/BAAGM7UzhGpDFidWaX+EQynK8gVZIQ0d8M8X28/NEdyrADNFgpqV63nawoRJllVgIYy44gYI+5lcFh1lD5zqcjZNxhfcuxmZgDg8/FQGXeixIqoUYRIzV4ikiFE9PUbQsRWuuuRHwLY580A4+uQyfYS0aqfT7w5huYG6rLJ4soR8XA8WEFIjgjxZoaEyBzjoSe60dNrD4nkCrJn2eyrb4wAAEplxRQZ7FyS4r5eoFACD2C5mjFfM9RjhUsGuSB6S0zIwSZE9NsRTcJRWhqipmJklNAMm8ApZ4vYX3VUnKEZAEgUc+AL9vcpaCoGhq1wSjvj2gQXtppD4/zMfBlnsirbRt3ofFqCgONW60Kk7HBE6umqCuhWvMZcq8LMyOFG+TZsb/NuOSJctZuxxDmECOM41XREHDki4xEivEcIR/TIOZnruKtmvIQIhWaIuQE1NJtj7O1297ooFN2OCKA7G4A9P6StydqU2AmvIU02hUixx2p2NsgHkWN+zYyEVUXR0N1bADQN75X3ICmXsEVowJOZxTXXrjChECVbMDu7sh08y7yIgOo9UsDmiGgaWlT9fEI0BDEZ8XRE4EpWtUIzfDXfpcwJmNcaRktjEKVD9v+loq31CRHzWtVUDolxc4RwbSHA5nOENatqRqhWCBmOSKGoQJbVMUt39XNOXIh4VXd4jbSf67COCCfwrpwRwF45I4Tqy9EhiCMRckTmGPmCe5POFSQUi9Y3fWODGhwpQ9M09DL5Ia1MfojGdCplhYg6MGI+PsAFzLbpgJ4jsmtfBtf+zysoV1S0aQUkZd2lmK/mUSwptoRQFiXHVJJkLCHCdvDsWbwM+Rr6Whci1RATZISrTkpgXiM0DZCr81fsOSL2ZFUzB0NWzM2+yAlIJfxYNC9iJq0CQAEi4slxbMJsF9es9V7F6ChCJBKAVjWcwpqMUkWFqqoQtWr1DOPQ5AqyvXQ3Xis0M7WOCAkRN+zQu1r5H7F1K8CHAvC3NSC4pM3zNQTxZoCEyBzDS4iwjogocmb4pVxRkS/KDkfE2lRUyTpXWFOQL8qoSAr8WSsJdIAP2oRItjeDG27ZZuaHLFOsEtuYJgGaVrOEV2aqVNRiGd3d+rEx0XIpkoubcb9/oefxAlQMVh2RJmayrL+9wZaE6nd8W7WOtxwRtr17mRORiPqxsCNqS1bNcD7EovXPT2GvpTFhKN8oQoTjeWgBffMPV/uI5DNls/7GCM0AenjG1lW1liMSmYQQ8fjm7lUOPNfhbaW53oIwMK8JS7/+fiz8/KWejglBvFkgITLHyFerY8IhwfaYkSMSDopoZOaPDI2Ua1bMaIwQMdp59/QWkZCs1+eDEeQZIVIczGKJlMbR8hAWtIVwasoqK/VDRQBW+KBvsIh//+8tuOmO16Eoqs0RAQApo1+nMWTloCxYksJ+IYanxRZrndX/CgAGqgPfmlUm3ySRMPNDAKurKuCumjEcEbaZmerzgec5lyOS5XyIR8YxyE2wNhuuaAmlYHyMjTykC4WQJqNSVpAetMI67MThbE6yJQPXEiKcKNgERT3NzAy8QgjUVdWNrUfIKDlAnCjMqRk8xNyEZPYcQlE0U3C0NATR2a1vWDmmaiYUFNCYsjaTgWFLiAgChybmOWdoBtD7esyrug3lQBDz5sfx+p4MihAQggL/wBAugd6jRA0HgL1WZQ4AxLSK+a39qRf6cOBgAQcOFvDya8NoytmTTyOQkIXf1jirsS2GZMyHpzJtGOSCkDgeJ8n9WFCtkJHKMsDxaGZG3A+KIfgqrCMythApZay1cNXNd+G8CPKc9b9UwR+EUGfZKwDw7HWrNcYagOAYjgIXCQLDafigoVKsID3CwdjaVCa0lMlLZmjGJ3Ke82sMhFgIatX1qbeZGVDDESEh4oLNEaFEVGKuQ47IHIJNSI1Ffeb8knzB6i0RDtrHtfcPldA7qG/arY32jZV1RAJQwWsq9r3Rj0C1y6mSjGNhu15eyoZnDPhtu1yPxTRrsxwascIIL782ZEtWBYBIVfxEeEtEiJEQViyOAxyHHWIKu4UEZKZRmFD1RwxHRAXQLYm20EygjmTVzICV9CtW8yJCQRFqUwN2CAn0cUHsa2jHeOA9ZtKUICA8imAA7KETNVdEdsT6nPwRa5PLMkIklQiM+k3blig5LkeEklXrgc0RoURUYq5DQmQOweaHREI+8xvxINPkKxQS0MQIkR170uYcmvYWe38JVbInlYagILPPau0utqTMY3JcfeZbTJPMxmjprCVEtu4Ysg2ZAywhYlTJcAIPzi/qQoSBZ0olRajgNQ2Nmv5tf4gLoGfAPtDPx5bvcpw5yI6HhmxewradIxjpt4SIj3EsFnZEcZ9/MW4PrgSXtK9jLLzyAEpcHUKE6fuhFUrIp63PKRSzRET/YMkUnM6pu+5zTkyIeCarUo6ICzEZBefXf67+9oYZXg1BzCwUmplD5JnuqZGwqG9ww2XbwDunI/LGXiuZtL3ZvqGwjgigh2diZSuPI7qgEeEW/RjJ0V+jyPsQUiU4iWkV81t7mmlLjlLZSvYw3oMmIeDnwVckqAD4cBAcx7mEiC8oAlVNI2gaGlAynZF+PoSevoI9R8Tn0Oc8D6gKBGh4bssAntsygBPlfpxdfTqYYITIvAg2v6qXL8dj48gPgXs0PADkOR/CwdH/N/XFQzA/qWIJBd76oKLxIFDVhvuZTra18kMMggtakNuyB5xfhL81Wc/yAYzdIZTQEYJ+dFx5Acpd/YiftHKml0MQMwoJkSMUVdVsU3DrIVewNvZISPTMEQgHRSTjfvA8B1XVzJJWAGhvcQoRhyOiyWhici8al7RArDoiGSY008sF0bP0KJyw6xUAQHBxK0qd+vC5mCZhfzWhMp2t6AmY4E33gyWiyZjfFoGyV7+mMQ+lvSWEaFhEruoA+YM+oKqnBGi2ipl+LoiD/UVH1YxdiHCiAE1WwDNKiG0rH2Emyy6Zb81U8ZpsOxqC3/3z6OVCODnkFigsgXgYhvzjS2UUVWudiYYwsEd/b0a5MwAka5Tumse9ZQ2EeBj+1tSofUycuGamiAL4wPgE2VwhtKgVoUWtM70MgphxKDRzBPLUC3349DXP4Vf37R3XcYWC3RGJht0bXygogOc5NHh8Yx7LEQlrMhqZTT7c0YhgQO+x8ZqYggQeOYi4x78EwtIOtF5xNpJvPRZt73ubeUxMkzA0UkFFUtCYT+PK0nb8Y2kHUpq79XtEk7C8I2w2VjPCAhzHYTnjigQYwSVAsyWqDvAhSJJqihbAQ4hU80SEGkIk1mi1WV+xOI63rGvBsoUxbDxpfJuM4OGIHOLDCI3hiPiZNu9CqYxy3gppJRpCMFJBWOdrLEeE94mIrzsKwfnjmxHDiYIZcgB0N4SqPgiCGA1yRI5AHt10EBVJxWPPHMIl5y1EwD/6N2aDnDM04yFEjDBAYzJgm8vCcUBLk12IOHNEzj4+Bd/mLgBAJRQyvwnPawljW7qCHwePhgIOMsejtTGI+LpFwLqjoGkauIAPWllCTJOQL8roGyzhLKkbAjTEIOGt0kHXWiOajAXzrG/r7Df31csS5gThUNjadAWottLdfk4/hu1d4ncIAkOI8NAwrzWE//eOJXj9pn3m86kWq3sqx3H4+0uWudZaD2LA/fMYDkbHdL78CcuREaUKpDKTnBv0IxIq24QWAKxampjQGutBCAUgV8UhhWUIghgLEiJHGJqmoW/I+kbfO1DCwnn1TXi1J6t6h2ZC1TAAmycCAC2NQfhEu1OgyfbNbZ5PRrra0TO5oNF8vL0lhG07R1Bmemy0NFobFMdxEBMRSH0jiGkVQNOwZ38OcSYck9LcTc4ikLCoQURv9T47qv4t61rQO1CEKPJoLByAMS5PgGaGj2RBRLYaMmITYwN+b0ckGuTxpY8di4BfgLggDK1zRH88ZU/inSiiIzRTBo9KeOxzs5u9WClDUSwhwgf0pmqsEFm9LGHrBzPV8KEAUJ0p5JzkSxAE4YRCM0cY6awEicln6B0sjvJqO2yyajQsIhJ2x+5NRyRlFyLOsAzgzhEp7e8zb/uarNCI17GtTfYNypfUcyt80BCEgt37sxjhRw8fRCFDZMQQzzgiosjj/71zCd59/iJbNYqgaWa+SSUUghG3sDsi3kJE5GC6T75K1S3iedt1J4PP4Yj08iFEo2P3mLALkQp8GjMPxy8i5miqdtap09sunG3QRY4IQRBjQULkCKNv0F7Cys6BGQvWEQnXckSqvUUaHY6Is3QXcOeIlJlhd74my/qf12o/NuDnEXe0PheTVpJnTJOw50AWxRqGXRb6sYKmQRq0qnqEiHcCJtvF0g/VyvVgBMrooRn9vqZYG7xSnQUjxkLgxpk0XAsxaP9MDvFhHL967NJOPuCDXG3lHtFk+MAKER8KRfvP6dijUlOw2tqwfTHE2NS4RQRBvHkhIXKE0T/kECIDpRqvdGMIEZ+m1K6aCVk5IixeVr4qO4bTqUwvjsbajkhLY9CVwCgyCZcxTULfYAkis6Gy9POWA1HptTqz1qru4JiQUoBJMmWbSqWzTKt5Z/mu0dSsKkQ0RYVS7fIqxKduo/U5qkv6xQjeur6+hNeyoB8b0mT4GUeEC/jQyuT2nH1q27irrcYL212VHBGCIMaChMgRhtMRYQfSjUW+KGOlPIJ/Km3D4K0P2ObNGLDJqizzWrxCM+6SWgNfo+WIhIKirYEWmx9iYHdEdHeC3VANVACDrBA5NGTe9mqmBdgn6AZhCRG2rHSEyRHx18gRMRwRJV80e5pM5Tf+gKM6pvXoDpdzVIuKT/98w1DgZ9+j34ezT21DwM+jvTmEC9+2YMrWWwshTKEZgiDqh5JVjzDcjkhRrzqpo0QyX5CwThmGAA3Fnd2InOtOADVCM8mYCI4DNE1Po2hrGq8Qidnut7eEzBkyLY1u58IZmgFgCzEYFCDa2sXbHJEarbLZ0AzriLB9O9jS1lo5ItA0aKoKOWM1bZtSRyToA+sxnXbm4rqPlX1+oKpJE0xiLx8Qsbwliu9dfRJ8In9YSmnFhPWz9KWio7ySIAiChMgRh9MRKVdUpLMSkmO07AZ0R8TPbO5BuIWEMDCMA7duQrl7EBsSi/F0PoJ5LWH4PUqEncmq5jniYfB++zf59pYwtu/Sa1daPYWIPTQD1BAinIg882srD1ut1mu1ImeFSJCpxBFqNNoK1CjfBaphGUaITKUjEon6wP50F3XEar7WiRywRFhCtYQIV/05OPNeppPY+pUo7uuFGA8juHR883YIgph7kBA5gtA0zeWIALorMpYQkWUV5Ypqq6jwK4yQ0DScpRzEwf/aYj70lkAG/mOW4vR1LZ7ndPYRMWDzQwzWrWnEn58+iIBfwNErkq7nvRwRr9BMrDmGpa3NwKv7Xc/VDs1YQoINzYghbyHiDs1Ym7imqJCz0+OINCxsQmdbGwJ9A4i/58xxHasyE1yjjMDkPbq1TjdiNIR5Hzj/sF+XIIgjExIiRxA5ZkouS+9ACSvHaFBllO7azP9yBaGggGJJQZNWwjqp33aMUCziiguX1jyns4+IgZcQWbYwhuuuOhEBn/cQNyHoBx/0Qy1VzBwRL0ekZUESq962HPtefcF9jprJqqwjwsyUqTF+vWayKgBMoyMCACdedTE0VRt/JU7I470LvE1EEQRBzEYoWfUIgg3LsFUs9SSsmhUzzOauFEpm5UxUcw+gk9N5aKp35YqmaTVDM2zpLksqHhh1kqzhLoQ1GZymeQoRIRrWK2w89mmuxrd/W44II8R8tRwRZ44Ibw/NsI6IOIWOiHW9CeRxeAgRPjB2uI4gCGKmISFyBNHPCJE1RyXN2711CJGcWbprbe5qoWwKg5DmISoUFUq2xrkVVc9k9cDv4YjUg5FsGoBqy2VhEWMh8EE/Gs49ySZGhNgoM01qOCK+sB/OQ3iegyA4hIjIChHFnqw6S/pkcB4dTMMr58/ASgiCIMYHCZEjCLa1+4rFcbMVeT1CpFD0cESKZXPwHZu4ynbGlEesZFAWdbSKmaaJCRGeCZVEGIeGLQENLtTzVRrPPwkL/vkS+Nv1hl/RY5fUPK8tR4RNVvX7zHJlA1dYBm5HRJmmHJHJIETsVU0yL6DpXRtmaDUEQRD1QzkiRwiqqtkckZbGIFqbQtjfk8fAcBmSrLpmwbDkClI13GG5GGqxjEhI77IZZpyCwLwmFHf3AACkkRyCHqPKNWczMwa2h8h44JnOomyoKHzUfMRPXgVNVW1VGMFFrVj4uUshj2QhpmpXmPCidx8Rzi8iFBRsre+9hAjrqECxynf5UMB27pnEmavSt3wFViepdJYgiNkPCZFZjqZp+NEvXserrw+boQeOA5pTQbRVhYimAXsPZHHUktoCIF+UXTkXSqGCcLLqiDBOQaDDEiK1HBG2h4gQDULJ6SKJD/prVq+MBeuIsEKEC/gQXtHheQzHc/A1jO7AsDkirBDjfaIemmKmDDsH3gEe5bvVcNV05IdMFH8shAJEhCGjjwtCPmbFTC+JIAiiLig0M8sZTlfwyo5haJruigBAMu6Hz8fj2JVJ83VPbu6rcQadfMEtRFQmWTUEuxAxqC1EmDJY5pu3ryk+4aZZfNASMKwQmWwJKlfDteD8PrOBm4FXvw02NKPkS6YImy35IQAQDIq4K7AYT4utuDOwFMkkTb0lCOLIgITILGc4Y+9+ynHAWRv06aknHN1oCokXtg0iX3BXvhjki7ItURXQc0SMCbxssmqgo9G8LQ3XyhFhkj6bkqZrEGhv9Hx9PbC5KXYhUl+b81rUEiK8X6wvR4QJecnDWfP2rHJE/DwO8RE85WtDgfPV1eCOIAhiNkChmVkOOxX2onMW4G2ntVuj6H08NpzQjEc3HYQsa3h2ywDOPtW7k6WnI1IsoyGhb1hmaIbn4W9J6hUpmuWIqBUJnE803Q42NCPGw2i5/CwUd3aj4dx1E36vAhOaaQpoQDUnlK/RAbX+E3vrbc4IzTCMlawqMQ7RbElUBWD+ThgkYyRECII4MiBHZJaTZoaxNSQCrg3nLSdZXU//+nwvtGpJ7XC6jDf2ps1wTr4ow+8o0VUKFRy3KoWN61uR9OmvEyJBcIJghh3kkRzSz7yG3V/+Pxy6/WHzWFaIcD4B8RNXoPX/nQlfQ/1tyZ2wOSJHNVvio1Z/kHoZ3RFxhGY8ckTYZFW2pfxsGnEfdPxeJGKTFG8EQRCHCRIisxzWEUkwdrvRaGxeSxjLFuqbf09fEXu7cigUZXzrR6/ihlu248/PHAIAZPOS2xEplcHzHN530VKzv4YQ0fM0fNUqFCVbxNCjLwKahtwre6AU9cROtmqG802NscYKETmdtx6fpCNSO0dERMgVmhk9R0SerY5IwFpjLCJCHKWCiiAIYjZBf61mOawjkqx+y808/zp2f+X/cPBnj0CVZNssmJe2D+GVHcPI5vUci82vDqBYknGov+juVKpqUMsS1IpkJWBW26SzQ+jkISsvQsnpFSNsH5GpKmG1CRGmadi05Yj4RIRDzmTV0atmpFnqiLBOGeWHEARxJEE5IrOckYyVtGlsMCNPvgqtIiP38i6ohRKOvext4Di90ekrO4YxwDQ+29edx2u709A0uJJVAb1yBpy10fIRQ4h496BQ8iWg2V41Mx2OCJjW8tw0CRHOK1l1jPJd1hGZVcmqPh6LOyLo7M7j6OXJmV4OQRBE3ZAQmeUYjojfxyMY0DfUcteA+XzhjS5wd/0FyxYuwK59WRzqL9om9Kqqhj/9Ve8J4tU2XSlUbG3OhbGESLVfCDvwjpuiEfNs1Yzt8cAkc0QmmazKJrva+qfMIkeE4zj8y4ePQXdvAYs6qJEZQRBHDuMKzWzduhXr169HKpXCVVddZSZG1sPll1+Of/7nfx73Auc6I1Uhkoz7wXEcNMXd0TS/fR/WLbB6cCiK/eeyt0v/Fu/piBTLustRxQjN+EZzRHAYHBH28cnmiHCcq3KG8+sVQHX1EfFwVDhRqCmcZgq/X8CSBTHwExmaRxAEMUPULUTK5TIuuOACrFu3Dps3b8b27dtx66231nXsQw89hD//+c+45pprJrrOOUm5oqBY0jd8owpCznjPlVnZOvZmnQi6NyjFKUQMRyRVS4h45IhMsxCZbGgGcIsJY83jnTVjIMTDE27cRhAEQVjULUQeeOABpNNp3HjjjVi2bBmuvfZa3HLLLWMeVywW8YlPfALXX389ksnkZNY657AnquqbtJLJe742IWpobbK6afp8PFKOpMXmuFswqIUylALriOjOSq3QjOrliExVsqooeJ5rssmqAMAJ9vMaJcF19RHxCO34RpltQxAEQdRP3UJky5Yt2LBhA8JhPS6+du1abN++fczjrrnmGhSLRYiiiD//+c9jhnPK5TIymYzt31yFTVQ1SnfZahLWtVAKJRy3usG8f/SyBFYts8+eSYXdm7xSKEEpWLNWjGRVIRLy3IBlU4hMfY4I4O2KTLqhGezdUQFL3Dj7iDj7tADeQqSWY0QQBEGMj7qFSCaTwZIl1qh1juMgCAKGh4drHrN//37ceOONWL58Ofbv34+rrroKf/u3fzuqGLnuuuuQSCTMfwsWLKh3iW86vBwRtr8G205dyZdwynFNMKIIp57YjKOW2IfBxQPuUIJarEDNW+EeIzTD8RwCC/WyYF+TdR7TEZGnPjQDeAuRqchBcTotxjl9Ph6CYH0uYyWrGtTKoSEIgiDGR91CRBRFBAL2qarBYBCFQqHGEcCtt96K1tZWPPzww/jqV7+Kv/zlL3j88cfx8MMP1zzm6quvRjqdNv8dOHCg3iW+6RhhhYjpiFhCxN9uOSBqvoT5bRF86WPH4jMfPBonHN2IFYstARGL+BDgPKpmimUoecsRMYQIALS97xw0X/IWdHz0Xdbrq0JEnYZkVcBdOcP5RXBTkHzpyhGphmY4jrO5It6hGbdLQo4IQRDE1FD3DtLQ0ICtW7faHstms/D7a1cOdHV14W1ve5spYGKxGFasWIG9e/fWPCYQCLgEz1RTGUjrPThKEkIrOhBZOTtdlzTbVTXmDs04HREAttLNplQAyxfFsGtfFqcc3wRt/yHXNdRCGWrZuo5RNQMAvlQUybesAQDwoYBeYVNtaGavmpnC0EzA/vs0FfkhQO0cEUDPE8nmdYen3hwRMUk5IgRBEFNB3UJk/fr1+N///V/zfmdnJ8rlMhoaGmoes2DBAlseiaqq6OrqwqJFiya43KlBGsxg8IHn9TsCP2uFCNvePRnXN2Ql7e2IsHkeBhzH4TMfPBqH+ovoaA2j+79fcr1GLZbNtu3guJolqUIkaCv1teWIiNPriEwFzhwR1sVh27z768wR8ZEjQhAEMSXUHZrZuHEj0uk0br/9dgDA9ddfj3POOQeCICCTyUCS3CPoL7vsMtx777343e9+h66uLlx99dUol8s4/fTTp+4dTAA2+VFj3IDZBhuacToinCjA32Qloyp577Jen8hjQXsEPM9BLevigRN4oBruUAqWuOBDAc9SVcAK2ailCjRFsc2a4acxWXUqElWB2qEZAHWEZrwcERIiBEEQU8G4ckRuvvlmXHnllWhtbcWdd96J66+/HoBeQXP//fe7jlm5ciV+/etf49///d+xYsUK3H///bjnnnsQi82src3a/2rJLaBmC+msvrZQUDCrOYxkVTER0ZtqVTdqNs+jFlpFPx8X8IEP6uEvtViGWnVTjIF3XrC5I0q+ZOsjMpU5IoJTiExVaMaZrMqcN8KU8Aa8pu86hAgfDkyZQCIIgpjrjGsHufjii7Fz505s3rwZp512GpqbmwHoYZpavPOd78Q73/nOSS1yqmE3EbU8O4WIpmlmaMaomFElGWo1jGJMfuUjQahlydaUDNCn4yr5EsSENbxOrQoRPuADJ/BQCyXIuSK06mfAig0nQjRk3lbypcNWvjt1oRnvhmYAcMrxzXh5xzCWzo+iucH9GTjzS6hihiAIYuoY91/5jo4OdHR0TMdaDht8cPYLkVJZQUXSq1wSZjMzpodIXBcYQiQIeSgLtViGpqrgeB6aqmLfDb+F1DeCtr8/B7HjlwMA1IouHni/z9zgNeb9s4mqTpyOiBmaEfia4ZyJ4MwRma7QDCtwjl2Zwo1fPgk+kffsluoMzYjUzIwgCGLKmLod5AjC7ojMzhwRr0RVtoeImNAdEVMgaBrUon5MpW8EUt8IACD3yp7q05oVmvGLEELuMAw/miPCCpFc0aya4aeoq6q5BmfVzFQJEWd4xe/sqCrUbNnuEiLkiBAEQUwZc1KIcILVSny2OiIHDlqiw6uHiOmIMC6G0apdq1hhEyVrlNvKQLWPHO/3gQ+7hch4HBEjR2Qq80MAr6qZaXJExrNuhxChihmCIIipY04KEcD6pj1bhcimF/vN20cvTwKw9xAxckTsToXRbMwSInJViKiMOOEDPk9HZLQcEb5GjshU5ocAHlUz0yREnI7IqMeSI0IQBDFtzFkhwhlCZBZWzQwOl7FjTxqA3pTM6JCq2EIzuiPChlO8HRFdvLC5IJxfhNjgznPwt6VqrskpeIzQzFT2EAE8qmYCU5Ss6mpoVr/AceeIkBAhCIKYKqZ2FzmCMHIRZmMfkU0v9cEYx3P6uhbw1Z4fco1kVQOr/bolRNRSRa+2YR0Rvw+JDUdDGkhDHslDiIYQXNyKyOqFNdfkSlatXmMqe4gAh9ERGUdoxlU1Q0KEIAhiypjDQkTf4DRFhSYrUzbKfrKoqoanq2EZjgNOPaHZfM6eI1INzTC5HuZAOkZ0AHqeiFG6C+gugxAOoPWyM+tel90RKUBT9IqeKc8RcZbvTlnVjKOz6njKgh2OiBALT8WSCIIgCMzh0MxsLeF9fW8GgyN6r5CjlyeRSlhCQ05Xu6oGfOaGLUTsuRuAvf06UBUOttDM+Dd3Pug3N2R5xBJE0y1EpmvWzPgcEYeImcJyZYIgiLnOnP2LOltLeF/cNmjePu3EZttzRr6HGLPEB9sN1cgRYd0PAJAzDkdkAps7x3GmKyKP5KzHpzg0w/lFs/08ML6k0lHPO0pn1TGPZUSMkSRMEARBTA1zODTDtHmfAUek3DOIzOY3ED9pBQLzmvR1qBq2vDYEAPCJHI5daSWPappmrpNnKl68ckS8HBF2451ot1IhEoSSKTjmzEztrxDHceCDfrPt/HSFZsZVNcNzmPfRdyL36l6kNq6dkvUQBEEQOnNYiDCOyAxUzvT+6jGUuwdQ3NmFhf9yKQBgX0/OnC+zalnSnC8D6C3bjQxW1tHgbX1E9M1bdeSIyNkiRCa/cqJNwrzKe6faEQFgEyLTNmtmnAIqsnLBrJ3STBAEcSQzd0MzwZlzRDRZQblHD8GUDw6ZDsPL24fN1xy/2l5Ky66RFRK8TzQdDrWWI5ItTDo0A9QQItOQ5Mv+bKasfNdZNTNF5yUIgiAmx9wVIjOYIyINZ013A5oGaSgLAGZYhuOAtasabMeMlmxqCASzfNezaoYZUjdRR8SjWmSqk1UBey+RWdFZlSAIgpg25qwQ4WZwAq/Un7bfH0ijd6CIg/16F9RlC2OIR+0bsN3RsG+iRmt2pVDSZ8pIztCMvWpmogmg4RXuYYdTnSMCMAmhHDdq2/nxYKt84abHySEIgiDGz5z9Wsg6ItphFiKVgbTr/suD1o/iuNUNzkNqhmYAJmSianoDM5cjUnA1NJsI4VUL9fyNkuUgTceGnjrreMiZAiKrFtr6pEwGdp2c31dzwB1BEARxeJnDQoTNETm8oZn8wRHb/XTXELaXGCGyyt1qnRUiztCKLWGV6XpqPuZoaDbRqhleFBBZsxjZzW9Y55oGRyQ4vxkLPnnRlJ6TFSLT4eIQBEEQE2POhmZsDc0Oc9VMrmfIdj/TNYRd+zMAgMZkAC2N7nCENoqjwSaRqvmSq7OqWpag5IrW8ZMoiY0dv8x2fzqqZqYDuyNCQoQgCGK2MHeFyAzmiChDGdv9ykAasqwnr65elvAMG4wemrE3NVMdjggAyNWEWGByJbHhFfPtDxhJt7MctikZOSIEQRCzhzksRGamfFdTFIiFgu2xqFIGX93QVy1PeB43WrIq2+BMKVZcjgigJ8QaTKZJGCcK9u6iR4YOIUeEIAhiljKHhcjMlO9WBrOuD10AENP0Naxe6i1EtNFyRNieKNVpu67jq0PqwHOu2SnjpeOj7wTnE8GH/Ig6QjWzFbaz6lS1jScIgiAmz5z9izxToZmhfQPWdWEpwZRWRry9AdGIt1thn547uhDxckQMhFBg0hUjgfZGLP36+6FpGoTQ1FS1TDc2R4RCMwRBELOGOeuIsI2yDqcQGdhrCZF0JG7eTmoVrK4RlgEAtTxKsqqjS6yXI2IQXbt0XOutBR/0HzEiBHB0oz2C1k0QBPFmZ+4KEZ4zQxyHs49Irsdq4x5ZtdC8nVTLWL1sFCEyqiPCiCo2R4S3Ox+cKCB1zokTWveRjhiPIL5hNcRUFMlTj57p5RAEQRBV5rRHzQd8UMqSrUHXVKNpmi0UogxbFTOtJy7F8AtbAQBNvITli2K1zzNajgiTeKvkS2Yli5iM2qplEqceDV8yirlK66VnzPQSCIIgCAckRDB9oZlcQcJ3f7INqqrh0/+wGsm4H4FqxUyF49F4VDuGRQGQFSyJafCP0pPDVr7rr50jomTz5m1fQ9wmRFJnnzDp90QQBEEQU8mcDc0AlpOgliVo09AP44VXBpA4eBCNvQfx+4f34dkXDiGm6uPty6EwOJ6Dv6kajknnrMoWD+pNVpUzTOOykB/xDasBjkPzxadDjLuH1hEEQRDETDLnHREAQHVQnHPSqzOsMl6Gd3TjAmkfAOChl1W89roPRnAgtrQN/7+9e42N6jzzAP4/Z+7j29jG2GAGMLgk3Bx2XSssVInakBapsMtWXSkCKVLaJLRIaenFEu626reEVlGElK5SIbGBfEi1baUItRXqLQqr7sppTBNa12xwwDYGG7CNmRl7PPd3P8zMmXPGczkzNpwZn/9PsjQznjN+41cnfnje531eALC3NiJy+x5EPIHwxDSc3tU5P0uzNJO160OyW5NH9gqBeCDTo0S2WdH6b09i9Zc+o2noRUREVClMnhHJv3MmOHwL1/79PzH+H+c12YhSxG/dVR5/IXITnYE7yvN1n90BAHB1rtX8zHzSY5DsVkjZRaiSpBSsag6kS/XLYBBCRESVioFISnYg4r90FSIcRej6JO7+4r9L/uxYLIHAnPYz2xPJbEWisR7ODa0AAHdnu/L9hU8m8n5eenz52rOrl2eU19gvg4iIKpypAxFJ0whMGzSEb04pjwN/GcbCtfxBQi6TUwuwJ3L382j5zHZlycfW0qC0TF8YmYSIxXNek96Sm+/AulyBCFuZExFRpTN1IKL+oy6y2rxnN+u681/vFWwUlu3GxDwcYnFQIWQZ9Z/eojyXJAnuTyWzIiISQ2j87qJrgExGJLuOJU29hVd5jRkRIiKqcAxEUrKXZuJZvUWiM34EPx7X/dk3JufhzBGI1O3YCGutS/Oaa3NmeSaYY3lGxBNKpkR25A4u1E3N0pgRISKiSsdAJCU7EEkshBe9PzrlW/RaPuMT83AiE4g07N0B99b1aDm0Z9F73Z/KFKwu5ChY1Z68W8LSDDMiRERU4Uz9l0q9nJF9Am+ubqvR2cCi13JJJATGJ+exV6SWciwyWv51b96twLamelib6hC7F0Bo9DYS0ZhmWUVE8ndVVf5bchWrMiNCREQVjhmRFHVGRCSEEohYG2qU16P39AUid2dCiEQTSkZEz4m3rs3JrIiIJxCZvKf5nubAu1KKVZkRISKiCmfuQER9WJxq10wiEgVSjVZtqz3KEfIxnYHIjYk5AFCKVfWc9qo+AyYeDGm+V6i9u/I6MyJERFSFzB2IaJZmVIGIqj7E4nLA2pQ8jC56L6CrFfzIzTlIQsCBZMt2i7t4ICKr3hMPautTCrV3L/Q6MyJERFTpTB6IqJdmMjUh6voQ2WmHLRWIiGgM8bnMWS75DI/6NYWqso5AxOJ2Zn5+ViBS6ORd5XpmRIiIqAqZOhCR8tSIJBZUgYjLoQQiQPE6kfmFGG7eDmq27mb3JMlFnTWJzxdamsm3fTdXjUjuoIWIiKhSmPqfzOosgno5Rt1DRHbZIddl+n7EZvy4/b9/R2jkNlqPPAVXqlV72iejfggBOKAqMNURiKizJomFrEBEz9IMMyJERFSFTJ0Rkd0OILWZRZ2F0NSIOO1KjQgABD66hsDAVURn/Jh998NFn3l11A8A2oyInqWZmszSzKIaEV3FqqwRISKi6mPqQESSZaU2Q137oV2asWuWZuavjCmPQ6N3FhWvXh1ZHIjIrsXZimzq5ZvsQCR9zgxQqI/I4mCHnVWJiKjSlRSIDA4OoqenB42Njejt7dW1g+TgwYOQJEn52rdvX9mDfRAsqXbrmoxIKBMIyE4HbI2ZQASJzH9zfG5Bs6V3IRTD+OQ8AKC1zpL5GXqWZlTvyS5W1ddZdfHrss2S451ERESVQ3cgEg6HcfDgQXR3d2NgYABDQ0M4e/Zs0esuXbqEv/3tb5idncXs7CzOnz+/lPEuu/SSiIjElD/42RkRucaZNxOxMHpbefzJWADp2GxtQyYIkFU7YvKRLLJS51Gwj0i+s2ayD72zyJAsDESIiKiy6Q5ELly4AJ/Ph9deew2bN2/Gyy+/jDNnzhS85ubNmxBCYMeOHfB4PPB4PKipqSl4zcNmUR1AF59LBgDqYlWLyw5JkjTLM2qh0TvK449HMmfRrHJnfrV6akSATMFqwe27eTIikt0KqLq38uRdIiKqBroDkcuXL2P37t1wu90AgK6uLgwNDRW85s9//jPi8TjWrVuHmpoaPPPMM5idnS14TTgcht/v13w9SJoi0flknYi6WDVde6FZnlEJjSUDkWg0gf4PpwEk4wGPPbOEo2fXDJDpJRIPhiFUS0B6ds1IkqRZnmF9CBERVQPdgYjf70dHR4fyXJIkWCyWgoHF1atX0d3djd/+9rcYGBjA6Ogovve97xX8Oa+88goaGhqUL6/Xq3eIZcmVEclemgEAW7MqEJEkZSdNeGIGiXAU71+eQmA+GTD84/ZmyNFM8GBxFy9WTb4vFbAIoW2wFi4eiADaLbzMiBARUTXQHYhYrVY4HNp/2TudTgSDwbzXnDhxAhcuXMD27duxdetW/OhHP8Ivf/nLgj+nr68PPp9P+RofH9c7xLLkyogoSzNSpvbC2lSvvM/hbYF7y7rkEyGwMHYHf/ifSeX7T+9do82q6MyIaHqJqJZnEqpdM/mKVQFtIMKMCBERVQPdgUhTUxOmpqY0rwUCAdjt+v61DwAejwfT09MIh8N53+NwOFBfX6/5epAKZURkhx2SnKy7sLc0KO9zb1kH18Y25fnYX8YwOZUMYjo31KHDW6dswZWsFt39PDTdVVUFq0qNiEVWDuDLRV2wyowIERFVA92BSE9PD/r7+5Xno6OjCIfDaGpqynvNl7/8Zc01H3zwAdra2hZlVoykyYikeomkt++q+3+4t3hR170F7ke9aHyyC86NmY6qs/93S3n89GfWJj8jmP4MByRVEWkh6t016l4i6aWZQtkQQLuFl83MiIioGugORJ544gn4fD689dZbAICTJ09i3759sFgs8Pv9iKpqItK6urrwrW99C++//z5+/etf4wc/+AGOHTu2fKNfBpqMyHxWRkS91GGR0Xb4c2h/4YuwuJ2wrWpQvu8KzgEA3C4Luh5pTH5WamlG746Z7Pdql2ZSgUiB+pDkeDPXc2mGiIiqge6/VlarFadPn8bhw4fR29uLeDyOixcvAkgGHKdOncKhQ4c01/T19WFsbAxPP/00Vq9eja9//evo6+tb1v+ApbLUajMiiVgcIpbsilqotkOSJNhaGhAen0JtPAKLSMBT74IsSxDxuNINVU9XVWUsmozI4qWZ4oFI5vtcmiEiompQ0l+rQ4cOYXh4GAMDA9izZw9aWloAJJdpcrHZbDhz5kzRfiNG0harhjQ7Ziw5DpJTs69KBiISAI+IoK7Gk/ycoPb0Xr1yFasKIZRi1WJZDharEhFRtSn5r1V7ezva29sfxFgMIVkskF12JBYiyYyIur17kWyGTVXA2ijCqK9JZiQ0h+bp6Kqaee/i82ZELI50u9biGREWqxIRUXUx9aF3aZaazHkzmh4iRTIithaP8rgxEUZtKhBRL6vo7SGSfO/ipZmEqstrsWJVCzMiRERUZUz51yq4EMPN2/O4PR3C5vV1sNQ6EZ32IRGKaE7hLbasYl+lzYg4c2RElro0E53KtI23egq3x1dnTJgRISKiamDKv1aDV+/jzC+GAQBf+sJ67KzJ7JyJTGf+8BerEclemrHWpjMi5QUi6lN60xmR8O17ymv2Nc0Fr5dVO4DkEnbrEBERGcWUSzOtqzJLIHemQ5qdM9HpzNk2xWpELC4HYqmGbo0JdY2IquC1hIBAslqUU37TwUxkckb5vqMtf88WAKjZsg7uR7xweFtQt6tT988lIiIyiikzIq2rMpmDO9MLsLRnnkdVGZFiNSIAEHK5URuJoBYxwJYsKlXXiMglFKsCycAlFo4qSzPhSVVGpEggIlktaH/xiyX9PCIiIiOZMiPidFjQUJfMPNyZDmm28GoCER3LKnP2TBBTE07Wl0RUwYOtsbaksaWXZ+LBMIQQiKSWZqwNNSVlV4iIiKqBKQMRAGhtTgYQgfko4qrzcqIzmaWZYjUiAHBfzgQHjoXkAYChsTsAAMlhg721saRxKRmURALRu/eVZR77msLZECIiompk3kBEVSfii+f+NejJiEwLVbByP4Do/TnEfPMAAKd3NSS5tF+xOusRvDahPC5WH0JERFSNTByIZJZU7oVyH0qnp0bkdixTZhOd9inZEACag/H0Uu92Wbg2qTwutmOGiIioGjEQAXB3QeR8T7FdM4mEwERIFYhM+RAau6s8d24oPRBR16ssXM9kRIoVqhIREVUjU+6aAbRLM5OBBLZkfd/e1li0KdhCKIaIkOCXbKgXUYQnZ5STcgHAuX51yePS9BLxJ2tOIEuwt3pK/iwiIqJKZ9qMyKpGB2Q5uSQzeS+iyX44N7Ri7QvFt8EG5pOH0Y3KdQAAEYkpO2ZszfWwqhqM6ZVrOce2qoGdUomIaEUybSBischoaUpmH+7OhOD57D/AUuOE58nHsO7YP8PmKb7tNjCfzH70W1uRkLR1JuXUhwCAq2MNmj7frXmNhapERLRSmfqf2a2rXLgzHUIkmoDUvQ0dn9sFScpduJpLOhDxy3b4N3XAc+268j3n+vICEQBo+vynIRICs3/4CwDAtWlN2Z9FRERUycwdiDSrWr3PhNDkKa1hWGAuUw8S3bUV8q2bymm55RSqpkmShOb9PXCsbUbs/hwa/mlb2Z9FRERUyUy7NAMsbvVeqnRGBADqmmux6l/2ALIE16Y1cLQvbbutJEmoe2wzGp98DJLVsqTPIiIiqlTmzohoDr9bWiBSW2NFwyOPorZrE2SHraQlHiIiIrMydSDS1pLJiEzcKScQiSmP61In7+ppC09ERERJpl6aqa+1K4ff3ZiYgxC5G5vlo64RSQciREREpJ+pAxEA2NCe3KYbDMUxdS9U0rWBYDIQcdhlOOys4yAiIioVA5G1NcrjsVvzJV2bzojUupkNISIiKofpA5GN6zKNy8Zuzem+Lh4XmF9I1ojU1TIQISIiKofpA5H1azOByGgJgcj8QhTpkhLWhxAREZXH9IFIfa0NTQ3JnS43JuaRSOgrWFUXqtbXmHrzERERUdlMH4gAmYLVcCShu5+IeutuLTMiREREZWEgAmBju7pORF/BqqarKmtEiIiIysJABMCG9szOGb11IppAhBkRIiKisjAQAbC+vfSdM35NjQgDESIionIwEAFQ47KiPrW8MuuP6LpmTnPODAMRIiKicjAQSalxJXe+BBdiRd6ZpK0R4a4ZIiKicjAQSXGnApFwJIF4PFH0/ZoD79hZlYiIqCwMRFLcrsxZMfML8aLvT2dE3E4LrFb+GomIiMrBv6Ap6aUZQN/yTDoQYX0IERFR+RiIpLjVgUiocCASjSWwEEpmTbh1l4iIqHwMRFLczkwgMh8sHIjMsZkZERHRsmAgkuIuYWlGvWOGPUSIiIjKx0AkpZSlGe05M9y6S0REVC4GIinaYtXCu2bUJ++yRoSIiKh8DERStNt39S/NsEaEiIiofAxEUkqpEfGzRoSIiGhZMBBJKaWPiHpphn1EiIiIyldSIDI4OIienh40Njait7cXQgjd10ajUezcuRPvvfdeqWN8KDTbd4sEInNB1ogQEREtB92BSDgcxsGDB9Hd3Y2BgQEMDQ3h7Nmzun/Qj3/8YwwODpYzxofCZpNhsyV/HUV3zaQyIpIE1Lq5a4aIiKhcugORCxcuwOfz4bXXXsPmzZvx8ssv48yZM7quHR4exquvvoqNGzeWO86HosaZLFgtumsmtX231m2FLEsPfFxEREQrle5A5PLly9i9ezfcbjcAoKurC0NDQ7quPXr0KE6cOIENGzYUfW84HIbf79d8PSzpgtViSzN+njNDRES0LHQHIn6/Hx0dHcpzSZJgsVgwOztb8Lo333wTPp8P3/nOd3T9nFdeeQUNDQ3Kl9fr1TvEJUsHItFoAtFYIud7wpE4otHk91gfQkREtDS6AxGr1QqHw6F5zel0IhgM5r1mamoKfX19OHPmDKxWfbUUfX198Pl8ytf4+LjeIS6Znp0zvkBEecxAhIiIaGl0V1o2NTUtKjYNBAKw2+15rzl+/Di++tWvYteuXboH5HA4FgU8D0t2L5GGusX/bWMT88rj1lXOhzIuIiKilUp3RqSnpwf9/f3K89HRUYTDYTQ1NeW95u2338brr78Oj8cDj8eDP/3pTzhw4ABOnjy5tFE/INrzZnIXrI6MzymPN3nrHviYiIiIVjLdGZEnnngCPp8Pb731Fp599lmcPHkS+/btg8Vigd/vh8vlgs2mXaoYGRnRPH/mmWdw/Phx7N+/f3lGv8zcTlWb92DupZnr4wHlcYe39oGPiYiIaCXTHYhYrVacPn0ahw8fRm9vL+LxOC5evAgguYPm1KlTOHTokOaa7O26TqcTbW1t8Hg8Sx33A1GszXs0lsB4amlmdbMTtW7WiBARES1FSd24Dh06hOHhYQwMDGDPnj1oaWkBkFym0aNSu6qmaYpVczQ1uzk5j1g82U12E7MhRERES1ZyW9D29na0t7c/iLEYTp0RydVL5LqqPqSD9SFERERLxkPvVIotzYyo6kOYESEiIlo6BiIqxfqIpDMiNpuM9lb3QxsXERHRSsVARMXtUu2ayTpvxheIYOZ+GACwYW0NLBb+6oiIiJaKf01V3M78GZFrN7htl4iIaLkxEFGxWmU47MlfSfaumSuf+JTHj3Q0PNRxERERrVQMRLKksyLqjIgQAn8fvg8AsFokbOmoN2JoREREKw4DkSzpnTNzwZhywN3dmZBSH7J5Qx0cdkve64mIiEg/BiJZvGuSu2HicYFTbw5hLhjFkGpZZlunx6CRERERrTwlNzRb6Q59fj2GRwOYuR/GxN0FvH7uiiYDwkCEiIho+TAjkqWx3oHjz21FfW3yHJnRW/P4eMQPAKirsWFdG/uHEBERLRcGIjmsbnbh+HPbUFejTRht7WyALEsGjYqIiGjlYSCSR3urG999fgc8dZkTdrd/ymPcgIiIiFYgBiIFtLW48N3nd2DHFg8ef2wVenY2Gz0kIiKiFYXFqkW0NDvx0rNbjR4GERHRisSMCBERERmGgQgREREZhoEIERERGYaBCBERERmGgQgREREZhoEIERERGYaBCBERERmGgQgREREZhoEIERERGYaBCBERERmGgQgREREZhoEIERERGYaBCBERERmm4k/fFUIAAPx+v8EjISIiIr3Sf7fTf8fzqfhAJBAIAAC8Xq/BIyEiIqJSBQIBNDQ05P2+JIqFKgZLJBKYmJhAXV0dJElats/1+/3wer0YHx9HfX39sn0uPRicr+rBuaoenKvqUm3zJYRAIBDA2rVrIcv5K0EqPiMiyzLWrVv3wD6/vr6+KiaUkjhf1YNzVT04V9WlmuarUCYkjcWqREREZBgGIkRERGQY0wYiDocDP/zhD+FwOIweCunA+aoenKvqwbmqLit1viq+WJWIiIhWLtNmRIiIiMh4DESIiIjIMAxEiIiIyDAMRIiIiMgwpgxEBgcH0dPTg8bGRvT29hbtg08P10svvQRJkpSvzs5OAJy3SjIzM4OOjg6Mjo4qrxWaH86dcXLNVb57DOBcGeX8+fPYtGkTrFYrHn/8cVy5cgWAOe4r0wUi4XAYBw8eRHd3NwYGBjA0NISzZ88aPSxSuXTpEn7zm99gdnYWs7Oz+PDDDzlvFWR6ehoHDhzQ/GErND+cO+Pkmisg9z0GcK6Mcu3aNTz33HM4efIkbt26hQ0bNuD55583z30lTOadd94RjY2NYn5+XgghxEcffST27t1r8KgoLRqNirq6OhEIBDSvc94qx1NPPSVOnTolAIiRkREhROH54dwZJ9dc5bvHhOBcGeVXv/qVeOONN5Tn7777rrDb7aa5r0yXEbl8+TJ2794Nt9sNAOjq6sLQ0JDBo6K0v/71rxBCYNeuXXC5XNi/fz9u3LjBeasgp0+fxje/+U3Na4Xmh3NnnFxzle8eAzhXRjlw4AC+9rWvKc8//vhjdHZ2mua+Ml0g4vf70dHRoTyXJAkWiwWzs7MGjorSrly5gu3bt+NnP/sZhoaGYLPZcPToUc5bBdm0adOi1wrND+fOOLnmKt89BvD/j5UgEong1VdfxbFjx0xzX5kuELFarYva4zqdTgSDQYNGRGpHjhxBf38/enp60NHRgZ/85Cf43e9+h0QiwXmrYIXuK95zlSXfPeb3+zlXFeD73/8+amtr8eKLL5rmvjJdINLU1ISpqSnNa4FAAHa73aARUSEejweJRAJtbW2ctwpW6L7iPVfZ0vfY5OQk58pgv//97/HTn/4Ub7/9Nmw2m2nuK9MFIj09Pejv71eej46OIhwOo6mpycBRUdq3v/1t/PznP1eef/DBB5BlGTt37uS8VbBC9xXvucqS7x7zer2cKwNdv34dR44cwRtvvIFt27YBMNF9ZXS17MMWjUZFS0uLOHfunBBCiKNHj4oDBw4YPCpKO3funOjs7BQXL14Uf/zjH8Wjjz4qvvKVr3DeKhCydmLkmx/OnfHUc5XvHhOCc2WUYDAotm7dKl544QURCASUr0gkYor7ynSBiBDJbU8ul0usXr1aNDc3i8HBQaOHRConTpwQHo9HeL1e8Y1vfEPMzc0JIThvlUb9x02IwvPDuTNW9lzlu8eE4FwZ4Z133hEAFn2NjIyY4r6ShKjSVmxLdOvWLQwMDGDPnj1oaWkxejikE+etshWaH85d9eBcVZaVfl+ZNhAhIiIi45muWJWIiIgqBwMRIiIiMgwDESIiIjIMAxEiIiIyDAMRIiIiMgwDESIiIjIMAxEiIiIyDAMRIiIiMgwDESIiIjLM/wNOfmjlXOEcvQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "1.4319341722810157"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "train_data      # 为DataFrame数据格式，（210，8）\n",
    "test_data       # 为DataFrame数据格式\n",
    "\n",
    "x_train = train_data.iloc[:, 1:7].values   # 为Numpy.array 数据格式， （210，6）210个样本，每个样本6个特征\n",
    "y_train = train_data.iloc[:, 0:1].values\n",
    "x_test = test_data.iloc[:, 1:7].values\n",
    "y_test = test_data.iloc[:, 0:1].values\n",
    "\n",
    "x_train = np.vstack((np.ones((x_train.shape[0], )), x_train.T)).T  \n",
    "x_test = np.vstack((np.ones((x_test.shape[0], )), x_test.T)).T\n",
    "'''\n",
    "x_train.shape[0] 读取第一维度的大小,即x_train的行数\n",
    "创建一个全1的列,然后垂直堆叠到 x_train 的转置上,最后转置回原始形状 \n",
    "(np.ones(x_train.shape[0], )): 210行, 1列     vstack((np.ones(x_train.shape[0], )), x_train.T): 6+1行, 210列\n",
    "转置回原始形状后  vstack((np.ones(x_train.shape[0], )), x_train.T).T : 210行,7列,第一列为全1\n",
    "'''\n",
    "\n",
    "history = {'Test Loss': [], 'Test Accuracy': [], 'Predict':[]}\n",
    "x1 = np.linspace(0, 210, 210)\n",
    "def model(X, Y, Learning_rate, iteration):\n",
    "    m = Y.size\n",
    "    theta = np.zeros((X.shape[1], 1))\n",
    "\n",
    "    for i in range(iteration):\n",
    "        y_pre = np.dot(X, theta)\n",
    "        cost = (1/(2*m))*np.sum(np.square(Y - y_pre))\n",
    "       \n",
    "        d_theta = (1/m)*np.dot(X.T, y_pre - Y)\n",
    "        theta = theta - Learning_rate*d_theta\n",
    "         \n",
    "        history['Test Loss'].append(cost)\n",
    "    print(cost)\n",
    "    return theta\n",
    "\n",
    "Learning_rate = 0.1\n",
    "iteration = 50\n",
    "theta = model(x_train, y_train,Learning_rate, iteration)\n",
    "plt.plot(history['Test Loss'], label='Test Loss')\n",
    "plt.legend(loc=0)\n",
    "plt.title(\"成本\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.show()\n",
    "\n",
    "y_pre = np.dot(x_train,theta)      # y_pre: 200行，1列\n",
    "error1 = (1/x_train.shape[0])*np.sum(np.abs(y_pre - x_train))\n",
    "plt.plot(x1, train_data.实际水量, linewidth = 2.0, color = '#667BC6', label = '实际水量')\n",
    "plt.plot(x1, y_pre, linewidth = 2.0, color = '#DA7297', label = '预测水量')\n",
    "# plt.scatter(x1, error1, c='#3AA6B9',marker='^')\n",
    "plt.legend(loc=0)\n",
    "plt.title(\"Errors\")\n",
    "plt.show()\n",
    "\n",
    "error1\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
